diff --git "a/competition/08b_InternLM_analysis.ipynb" "b/competition/08b_InternLM_analysis.ipynb"
--- "a/competition/08b_InternLM_analysis.ipynb"
+++ "b/competition/08b_InternLM_analysis.ipynb"
@@ -1 +1 @@
-{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{},"inputWidgets":{},"nuid":"0ea8b46b-839b-445b-8043-ccdf4e920ace","showTitle":false,"title":""},"id":"YLH80COBzi_F"},"outputs":[],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":2,"metadata":{"id":"63B5exAuzq4M"},"outputs":[],"source":["from pathlib import Path\n","\n","try:\n","    from google.colab import drive\n","    drive.mount('/content/drive')\n","    workding_dir = \"/content/drive/MyDrive/logical-reasoning/\"\n","except ModuleNotFoundError:\n","    workding_dir = str(Path.cwd().parent)"]},{"cell_type":"code","execution_count":3,"metadata":{"executionInfo":{"elapsed":368,"status":"ok","timestamp":1719461634865,"user":{"displayName":"Donghao Huang","userId":"00463591218503521679"},"user_tz":-480},"id":"zFulf0bg0H-9","outputId":"debdd535-c828-40b9-efc0-8a180e5830dd"},"outputs":[{"name":"stdout","output_type":"stream","text":["workding dir: /home/inflaton/code/projects/courses/logical-reasoning\n"]}],"source":["import os\n","import sys\n","\n","os.chdir(workding_dir)\n","sys.path.append(workding_dir)\n","print(\"workding dir:\", workding_dir)"]},{"cell_type":"code","execution_count":4,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{},"inputWidgets":{},"nuid":"9f67ec60-2f24-411c-84eb-0dd664b44775","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":589,"status":"ok","timestamp":1719462011879,"user":{"displayName":"Donghao Huang","userId":"00463591218503521679"},"user_tz":-480},"id":"DIUiweYYzi_I","outputId":"e16e9247-9077-4b0c-f8ea-17059f05a1c4"},"outputs":[{"name":"stdout","output_type":"stream","text":["loading env vars from: /home/inflaton/code/projects/courses/logical-reasoning/.env\n"]},{"data":{"text/plain":["True"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["from dotenv import find_dotenv, load_dotenv\n","\n","found_dotenv = find_dotenv(\".env\")\n","\n","if len(found_dotenv) == 0:\n","    found_dotenv = find_dotenv(\".env.example\")\n","print(f\"loading env vars from: {found_dotenv}\")\n","load_dotenv(found_dotenv, override=True)"]},{"cell_type":"code","execution_count":5,"metadata":{"id":"W2QyVreqhOGM","outputId":"68b9590e-1ac6-4c6f-e0c4-e273ec816419"},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>label</th>\n","      <th>title</th>\n","      <th>puzzle</th>\n","      <th>truth</th>\n","      <th>internlm/internlm2_5-7b-chat-1m</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-562</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-1124</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-1686</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-2248</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-2810</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-3372</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>甄加索是自杀吗</td>\n","      <td>不是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>甄加索有身体上的疾病吗</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>画作是甄的</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>甄有心脏病吗</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>车轮是凶手留下的</td>\n","      <td>不是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>2995</th>\n","      <td>哭泣者必须在晚上祭奠吗</td>\n","      <td>是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","    </tr>\n","    <tr>\n","      <th>2996</th>\n","      <td>尸体在湖里吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>2997</th>\n","      <td>哭泣者和死者有特殊关系吗</td>\n","      <td>是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2998</th>\n","      <td>是帽子的主人去世了吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2999</th>\n","      <td>死者受伤了吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3000 rows × 12 columns</p>\n","</div>"],"text/plain":["              text label title  \\\n","0          甄加索是自杀吗    不是  海岸之谜   \n","1      甄加索有身体上的疾病吗     是  海岸之谜   \n","2            画作是甄的     是  海岸之谜   \n","3           甄有心脏病吗     是  海岸之谜   \n","4         车轮是凶手留下的    不是  海岸之谜   \n","...            ...   ...   ...   \n","2995   哭泣者必须在晚上祭奠吗     是  甄庄哭声   \n","2996        尸体在湖里吗    不是  甄庄哭声   \n","2997  哭泣者和死者有特殊关系吗     是  甄庄哭声   \n","2998    是帽子的主人去世了吗    不是  甄庄哭声   \n","2999        死者受伤了吗    不是  甄庄哭声   \n","\n","                                                 puzzle  \\\n","0     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","1     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","2     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","3     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","4     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","...                                                 ...   \n","2995  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2996  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2997  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2998  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2999  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","\n","                                                  truth  \\\n","0     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","1     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","2     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","3     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","4     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","...                                                 ...   \n","2995  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2996  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2997  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2998  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2999  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","\n","     internlm/internlm2_5-7b-chat-1m  \\\n","0                                 不是   \n","1                                  是   \n","2                                 不是   \n","3                                  是   \n","4                                 不是   \n","...                              ...   \n","2995                              不是   \n","2996                              不是   \n","2997                               是   \n","2998                               是   \n","2999                              不是   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-562  \\\n","0                                                不是   \n","1                                                 是   \n","2                                                 是   \n","3                                                 是   \n","4                                               不重要   \n","...                                             ...   \n","2995                                            不重要   \n","2996                                            不重要   \n","2997                                              是   \n","2998                                              是   \n","2999                                            不重要   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-1124  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                             不重要   \n","2997                                               是   \n","2998                                               是   \n","2999                                             不重要   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-1686  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                              不是   \n","2997                                               是   \n","2998                                               是   \n","2999                                              不是   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-2248  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                              不是   \n","2997                                               是   \n","2998                                               是   \n","2999                                             不重要   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-2810  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                              不是   \n","2997                                               是   \n","2998                                               是   \n","2999                                              不是   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-3372  \n","0                                                 不是  \n","1                                                  是  \n","2                                                  是  \n","3                                                  是  \n","4                                                 不是  \n","...                                              ...  \n","2995                                             不重要  \n","2996                                              不是  \n","2997                                               是  \n","2998                                               是  \n","2999                                             不重要  \n","\n","[3000 rows x 12 columns]"]},"execution_count":5,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","df = pd.read_csv(\"results/mgtv-results_nv4080_r2.csv\")\n","df"]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[],"source":["import matplotlib.pyplot as plt\n","from matplotlib import rcParams\n","\n","def plot_value_counts(df, column):\n","    font_family = rcParams[\"font.family\"]\n","    # Set the font to SimHei to support Chinese characters\n","    rcParams[\"font.family\"] = \"STHeiti\"\n","    rcParams[\"axes.unicode_minus\"] = False  # This is to support the minus sign in Chinese.\n","\n","    plt.figure(figsize=(12, 6))\n","    df[column].value_counts().plot(kind=\"bar\")\n","    # add values on top of bars\n","    for i, v in enumerate(df[column].value_counts()):\n","        plt.text(i, v + 0.1, str(v), ha=\"center\")\n","    plt.show()\n","    \n","    rcParams[\"font.family\"] = font_family\n"]},{"cell_type":"code","execution_count":7,"metadata":{},"outputs":[{"data":{"text/plain":["['text',\n"," 'label',\n"," 'title',\n"," 'puzzle',\n"," 'truth',\n"," 'internlm/internlm2_5-7b-chat-1m',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-562',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-1124',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-1686',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-2248',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-2810',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-3372']"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["df.columns.to_list()"]},{"cell_type":"code","execution_count":9,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 19981 (\\N{CJK UNIFIED IDEOGRAPH-4E0D}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 26159 (\\N{CJK UNIFIED IDEOGRAPH-662F}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 35201 (\\N{CJK UNIFIED IDEOGRAPH-8981}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n"]},{"name":"stderr","output_type":"stream","text":["/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 12290 (\\N{IDEOGRAPHIC FULL STOP}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 30007 (\\N{CJK UNIFIED IDEOGRAPH-7537}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 23401 (\\N{CJK UNIFIED IDEOGRAPH-5B69}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m **********\n","internlm/internlm2_5-7b-chat-1m\n","不是      1670\n","是       1283\n","不重要       43\n","不重要。       3\n","是男孩。       1\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 19981 (\\N{CJK UNIFIED IDEOGRAPH-4E0D}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 35201 (\\N{CJK UNIFIED IDEOGRAPH-8981}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 26159 (\\N{CJK UNIFIED IDEOGRAPH-662F}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 22238 (\\N{CJK UNIFIED IDEOGRAPH-56DE}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 31572 (\\N{CJK UNIFIED IDEOGRAPH-7B54}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 27491 (\\N{CJK UNIFIED IDEOGRAPH-6B63}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 30830 (\\N{CJK UNIFIED IDEOGRAPH-786E}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 38382 (\\N{CJK UNIFIED IDEOGRAPH-95EE}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 27861 (\\N{CJK UNIFIED IDEOGRAPH-6CD5}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 38169 (\\N{CJK UNIFIED IDEOGRAPH-9519}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 35823 (\\N{CJK UNIFIED IDEOGRAPH-8BEF}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-562 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-562\n","不重要     1828\n","是        875\n","不是       257\n","回答正确      28\n","问法错���      12\n","Name: count, dtype: int64\n"]},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA+IAAAIgCAYAAAABTdNAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAABLFUlEQVR4nO3deVhWdf7/8dcNeLMJKCpbIprmGqhjalhuoyMiYzlZllpqMVoNZmmlOd8W00lMHVsmv2bjVt/UbCa3NB33NCW3YiwzUtOoUWxRuQUVWc7vj36e6Q5UKO4PIM/Hdd3XxTmf9znnfeBQvjibw7IsSwAAAAAAwAivim4AAAAAAIDqhCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAgn4puwFOKiop07NgxBQUFyeFwVHQ7AAAAAICrnGVZOnPmjKKiouTldenz3ldtED927Jiio6Mrug0AAAAAQDXz9ddfq379+pccv2qDeFBQkKQfvwHBwcEV3A0AAAAA4GrncrkUHR1t59FLuWqD+MXL0YODgwniAAAAAABjrnR7NA9rAwAAAADAIII4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHE4Wbr1q3q27evoqKi5HA4tHz5crfxnJwcjRw5UvXr15e/v79atmypV1991R4/efKkHnroITVr1kz+/v5q0KCBRo0apezsbLf17N69Wz169FCtWrVUu3ZtJSQk6N///reJXQQAAACACkUQh5vc3Fy1bt1aM2fOLHF8zJgxWrt2rd58800dOHBAjzzyiEaOHKmVK1dKko4dO6Zjx45p+vTp+vTTT7VgwQKtXbtWycnJ9jpycnLUu3dvNWjQQDt37tQHH3ygoKAgJSQkKD8/38h+AgAAAEBFcViWZVV0E57gcrkUEhKi7OxsBQcHV3Q7VZLD4dCyZcvUr18/e97111+vO++8U0899ZQ9r127dkpMTNRf/vKXEtfzj3/8Q3fffbdyc3Pl4+OjPXv2qH379srMzFR0dLQk6ZNPPlFcXJwOHjyoJk2aeHS/AAAAAMATSptDOSOOMunUqZNWrlyp//znP7IsS5s3b9YXX3yhXr16XXKZiwehj4+PJKlZs2aqU6eO5s6dqwsXLujcuXOaO3euWrRooYYNGxraEwAAAACoGARxlMnf/vY3tWzZUvXr15fT6VTv3r01c+ZMdenSpcT677//XpMmTdKIESPseUFBQdqyZYvefPNN+fv7q2bNmlq7dq3WrFljh3UAAAAAuFoRxFEmf/vb3/Thhx9q5cqV2rt3r/76178qJSVFGzZsKFbrcrmUlJSkli1basKECfb8c+fOKTk5WTfddJM+/PBDbd++Xddff72SkpJ07tw5g3sDAAAAAOZx+hGldu7cOf35z3/WsmXLlJSUJEmKi4tTenq6pk+frp49e9q1Z86cUe/evRUUFKRly5apRo0a9tiiRYt09OhRpaWlycvLy55Xu3ZtrVixQnfddZfZHQMAAAAAgzgjjlLLz89Xfn6+HZ4v8vb2VlFRkT3tcrnUq1cvOZ1OrVy5Un5+fm71Z8+elZeXlxwOhz3v4vRP1wMAAAAAVyOCONzk5OQoPT1d6enpkqQjR44oPT1dmZmZCg4OVteuXfX4449ry5YtOnLkiBYsWKA33nhDf/jDHyT9N4Tn5uZq7ty5crlcysrKUlZWlgoLCyVJv/vd73Tq1CmlpKTowIED2r9/v+699175+Pioe/fuFbXrAAAAAGAEry+rhBo+sbrCtn0+c59OLP5zsfmB1/dQ3aTRKsw5pVPvv67zRz9S0fkceQeHKah1goLa95PD4bjk8pJ0zQNz5RMSLkk6d+RjZW9frAvffyWHwyFn+LWq1XmIfK9p7tH9u5SjU5IqZLsAAAAArh6lzaEE8UqoIoN4dUUQBwAAAPBr8R5xAAAAAAAqIYI4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwqcxDfunWr+vbtq6ioKDkcDi1fvtxt3OFwlPiZNm2aXdOwYcNi41OmTHFbz759+9S5c2f5+fkpOjpaU6dO/WV7CAAAAABAJVLmIJ6bm6vWrVtr5syZJY4fP37c7TNv3jw5HA7179/frW7ixIludQ899JA95nK51KtXL8XExGjv3r2aNm2aJkyYoNdee62s7QIAAAAAUKn4lHWBxMREJSYmXnI8IiLCbXrFihXq3r27rr32Wrf5QUFBxWovWrhwoS5cuKB58+bJ6XSqVatWSk9P14wZMzRixIiytgwAAAAAQKXh0XvET5w4odWrVys5ObnY2JQpU1SnTh21bdtW06ZNU0FBgT2WlpamLl26yOl02vMSEhKUkZGhU6dOlbitvLw8uVwutw8AAAAAAJVNmc+Il8Xrr7+uoKAg3XbbbW7zR40apd/85jcKDQ3Vjh07NH78eB0/flwzZsyQJGVlZalRo0Zuy4SHh9tjtWvXLrat1NRUPfvssx7aEwAAAAAAyodHg/i8efM0ePBg+fn5uc0fM2aM/XVcXJycTqfuv/9+paamytfX9xdta/z48W7rdblcio6O/mWNAwAAAADgIR4L4tu2bVNGRoaWLFlyxdqOHTuqoKBAR48eVbNmzRQREaETJ0641VycvtR95b6+vr84xAMAAAAAYIrH7hGfO3eu2rVrp9atW1+xNj09XV5eXgoLC5MkxcfHa+vWrcrPz7dr1q9fr2bNmpV4WToAAAAAAFVFmYN4Tk6O0tPTlZ6eLkk6cuSI0tPTlZmZade4XC794x//0B//+Mdiy6elpenFF1/Uv//9b3355ZdauHChRo8erbvvvtsO2YMGDZLT6VRycrL279+vJUuW6KWXXnK79BwAAAAAgKqozJem79mzR927d7enL4bjoUOHasGCBZKkt956S5ZlaeDAgcWW9/X11VtvvaUJEyYoLy9PjRo10ujRo91CdkhIiNatW6eUlBS1a9dOdevW1dNPP82rywAAAAAAVZ7DsiyropvwBJfLpZCQEGVnZys4OLii2ymThk+srugWqp2jU5IqugUAAAAAVVxpc6hH3yMOAAAAAADcEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGlTmIb926VX379lVUVJQcDoeWL1/uNj5s2DA5HA63T+/evd1qTp48qcGDBys4OFi1atVScnKycnJy3Gr27dunzp07y8/PT9HR0Zo6dWrZ9w4AAAAAgEqmzEE8NzdXrVu31syZMy9Z07t3bx0/ftz+LF682G188ODB2r9/v9avX69Vq1Zp69atGjFihD3ucrnUq1cvxcTEaO/evZo2bZomTJig1157raztAgAAAABQqfiUdYHExEQlJiZetsbX11cREREljh04cEBr167V7t27dcMNN0iS/va3v6lPnz6aPn26oqKitHDhQl24cEHz5s2T0+lUq1atlJ6erhkzZrgFdgAAAAAAqhqP3CO+ZcsWhYWFqVmzZnrwwQf1ww8/2GNpaWmqVauWHcIlqWfPnvLy8tLOnTvtmi5dusjpdNo1CQkJysjI0KlTp0rcZl5enlwul9sHAAAAAIDKptyDeO/evfXGG29o48aNev755/X+++8rMTFRhYWFkqSsrCyFhYW5LePj46PQ0FBlZWXZNeHh4W41F6cv1vxcamqqQkJC7E90dHR57xoAAAAAAL9amS9Nv5K77rrL/jo2NlZxcXFq3LixtmzZoh49epT35mzjx4/XmDFj7GmXy0UYBwAAAABUOh5/fdm1116runXr6tChQ5KkiIgIffvtt241BQUFOnnypH1feUREhE6cOOFWc3H6Uvee+/r6Kjg42O0DAAAAAEBl4/Eg/s033+iHH35QZGSkJCk+Pl6nT5/W3r177ZpNmzapqKhIHTt2tGu2bt2q/Px8u2b9+vVq1qyZateu7emWAQAAAADwmDIH8ZycHKWnpys9PV2SdOTIEaWnpyszM1M5OTl6/PHH9eGHH+ro0aPauHGjbr31VjVp0kQJCQmSpBYtWqh3794aPny4du3ape3bt2vkyJG66667FBUVJUkaNGiQnE6nkpOTtX//fi1ZskQvvfSS26XnAAAAAABURWUO4nv27FHbtm3Vtm1bSdKYMWPUtm1bPf300/L29ta+fft0yy23qGnTpkpOTla7du20bds2+fr62utYuHChmjdvrh49eqhPnz66+eab3d4RHhISonXr1unIkSNq166dHn30UT399NO8ugwAAAAAUOU5LMuyKroJT3C5XAoJCVF2dnaVu1+84ROrK7qFaufolKSKbgEAAABAFVfaHOrxe8QBAAAAAMB/EcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGEcQBAAAAADCozEF869at6tu3r6KiouRwOLR8+XJ7LD8/X+PGjVNsbKwCAwMVFRWlIUOG6NixY27raNiwoRwOh9tnypQpbjX79u1T586d5efnp+joaE2dOvWX7SEAAAAAAJVImYN4bm6uWrdurZkzZxYbO3v2rD766CM99dRT+uijj7R06VJlZGTolltuKVY7ceJEHT9+3P489NBD9pjL5VKvXr0UExOjvXv3atq0aZowYYJee+21srYLAAAAAECl4lPWBRITE5WYmFjiWEhIiNavX+8275VXXlGHDh2UmZmpBg0a2PODgoIUERFR4noWLlyoCxcuaN68eXI6nWrVqpXS09M1Y8YMjRgxosRl8vLylJeXZ0+7XK6y7hoAAAAAAB7n8XvEs7Oz5XA4VKtWLbf5U6ZMUZ06ddS2bVtNmzZNBQUF9lhaWpq6dOkip9Npz0tISFBGRoZOnTpV4nZSU1MVEhJif6Kjoz2yPwAAAAAA/BoeDeLnz5/XuHHjNHDgQAUHB9vzR40apbfeekubN2/W/fffr8mTJ2vs2LH2eFZWlsLDw93WdXE6KyurxG2NHz9e2dnZ9ufrr7/2wB4BAAAAAPDrlPnS9NLKz8/XgAEDZFmWZs2a5TY2ZswY++u4uDg5nU7df//9Sk1Nla+v7y/anq+v7y9eFgAAAAAAUzxyRvxiCP/qq6+0fv16t7PhJenYsaMKCgp09OhRSVJERIROnDjhVnNx+lL3lQMAAAAAUBWUexC/GMIPHjyoDRs2qE6dOldcJj09XV5eXgoLC5MkxcfHa+vWrcrPz7dr1q9fr2bNmql27drl3TIAAAAAAMaU+dL0nJwcHTp0yJ4+cuSI0tPTFRoaqsjISN1+++366KOPtGrVKhUWFtr3dIeGhsrpdCotLU07d+5U9+7dFRQUpLS0NI0ePVp33323HbIHDRqkZ599VsnJyRo3bpw+/fRTvfTSS3rhhRfKabcBAAAAAKgYDsuyrLIssGXLFnXv3r3Y/KFDh2rChAlq1KhRictt3rxZ3bp100cffaQ//elP+vzzz5WXl6dGjRrpnnvu0ZgxY9zu8d63b59SUlK0e/du1a1bVw899JDGjRtX6j5dLpdCQkKUnZ19xUvjK5uGT6yu6BaqnaNTkiq6BQAAAABVXGlzaJmDeFVBEEdZEMQBAAAA/FqlzaEef484AAAAAAD4L4I4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAoDIH8a1bt6pv376KioqSw+HQ8uXL3cYty9LTTz+tyMhI+fv7q2fPnjp48KBbzcmTJzV48GAFBwerVq1aSk5OVk5OjlvNvn371LlzZ/n5+Sk6OlpTp04t+94BAAAAAFDJlDmI5+bmqnXr1po5c2aJ41OnTtXLL7+sV199VTt37lRgYKASEhJ0/vx5u2bw4MHav3+/1q9fr1WrVmnr1q0aMWKEPe5yudSrVy/FxMRo7969mjZtmiZMmKDXXnvtF+wiAAAAAACVh8OyLOsXL+xwaNmyZerXr5+kH8+GR0VF6dFHH9Vjjz0mScrOzlZ4eLgWLFigu+66SwcOHFDLli21e/du3XDDDZKktWvXqk+fPvrmm28UFRWlWbNm6X/+53+UlZUlp9MpSXriiSe0fPlyff755yX2kpeXp7y8PHva5XIpOjpa2dnZCg4O/qW7WCEaPrG6oluodo5OSaroFgAAAABUcS6XSyEhIVfMoeV6j/iRI0eUlZWlnj172vNCQkLUsWNHpaWlSZLS0tJUq1YtO4RLUs+ePeXl5aWdO3faNV26dLFDuCQlJCQoIyNDp06dKnHbqampCgkJsT/R0dHluWsAAAAAAJSLcg3iWVlZkqTw8HC3+eHh4fZYVlaWwsLC3MZ9fHwUGhrqVlPSOn66jZ8bP368srOz7c/XX3/963cIAAAAAIBy5lPRDZQXX19f+fr6VnQbAAAAAABcVrmeEY+IiJAknThxwm3+iRMn7LGIiAh9++23buMFBQU6efKkW01J6/jpNgAAAAAAqIrKNYg3atRIERER2rhxoz3P5XJp586dio+PlyTFx8fr9OnT2rt3r12zadMmFRUVqWPHjnbN1q1blZ+fb9esX79ezZo1U+3atcuzZQAAAAAAjCpzEM/JyVF6errS09Ml/fiAtvT0dGVmZsrhcOiRRx7RX/7yF61cuVKffPKJhgwZoqioKPvJ6i1atFDv3r01fPhw7dq1S9u3b9fIkSN11113KSoqSpI0aNAgOZ1OJScna//+/VqyZIleeukljRkzptx2HAAAAACAilDme8T37Nmj7t2729MXw/HQoUO1YMECjR07Vrm5uRoxYoROnz6tm2++WWvXrpWfn5+9zMKFCzVy5Ej16NFDXl5e6t+/v15++WV7PCQkROvWrVNKSoratWununXr6umnn3Z71zgAAAAAAFXRr3qPeGVW2ve3VUa8R9w83iMOAAAA4NeqkPeIAwAAAACAyyOIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjiAaq+wsFBPPfWUGjVqJH9/fzVu3FiTJk2SZVl2jcPhKPEzbdo0u6Zhw4bFxqdMmVIRuwQAAIBKzKeiGwCAivb8889r1qxZev3119WqVSvt2bNH9957r0JCQjRq1ChJ0vHjx92WWbNmjZKTk9W/f3+3+RMnTtTw4cPt6aCgIM/vAAAAAKoUgjiAam/Hjh269dZblZSUJOnHM9uLFy/Wrl277JqIiAi3ZVasWKHu3bvr2muvdZsfFBRUrBYAAAD4KS5NB1DtderUSRs3btQXX3whSfr3v/+tDz74QImJiSXWnzhxQqtXr1ZycnKxsSlTpqhOnTpq27atpk2bpoKCAo/2DgAAgKqHM+IAqr0nnnhCLpdLzZs3l7e3twoLC/Xcc89p8ODBJda//vrrCgoK0m233eY2f9SoUfrNb36j0NBQ7dixQ+PHj9fx48c1Y8YME7sBAACAKoIgDqDae/vtt7Vw4UItWrRIrVq1Unp6uh555BFFRUVp6NChxernzZunwYMHy8/Pz23+mDFj7K/j4uLkdDp1//33KzU1Vb6+vh7fDwAAAFQNBHEA1d7jjz+uJ554QnfddZckKTY2Vl999ZVSU1OLBfFt27YpIyNDS5YsueJ6O3bsqIKCAh09elTNmjXzSO8AAACoerhHHEC1d/bsWXl5uf/n0NvbW0VFRcVq586dq3bt2ql169ZXXG96erq8vLwUFhZWbr0CAACg6uOMOIBqr2/fvnruuefUoEEDtWrVSh9//LFmzJih++67z63O5XLpH//4h/76178WW0daWpp27typ7t27KygoSGlpaRo9erTuvvtu1a5d29SuAAAAoApwWJZlVXQTnuByuRQSEqLs7GwFBwdXdDtl0vCJ1RXdQrVzdEpSRbdQ7VSm47wo76xOb3tTZw+mqehstrxrhiqgRVfVuukuObxr2HVn0tfq1Ma/q/7IN+TlG+i2jrysQzq5bpbyT34jFebLJyRcga26K7j9H+TwqfHzTVYIjnMAAADPKm0O5Yw4gGrPyzdAoT1HKLTniMvWBbXpraA2vUsc841oosghxc+UAwAAAD/HPeIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhU7kG8YcOGcjgcxT4pKSmSpG7duhUbe+CBB9zWkZmZqaSkJAUEBCgsLEyPP/64CgoKyrtVAAAAAACM8ynvFe7evVuFhYX29Keffqrf/e53uuOOO+x5w4cP18SJE+3pgIAA++vCwkIlJSUpIiJCO3bs0PHjxzVkyBDVqFFDkydPLu92AQAAAAAwqtyDeL169dymp0yZosaNG6tr1672vICAAEVERJS4/Lp16/TZZ59pw4YNCg8PV5s2bTRp0iSNGzdOEyZMkNPpLO+WAQAAAAAwxqP3iF+4cEFvvvmm7rvvPjkcDnv+woULVbduXV1//fUaP368zp49a4+lpaUpNjZW4eHh9ryEhAS5XC7t37//ktvKy8uTy+Vy+wAAAAAAUNmU+xnxn1q+fLlOnz6tYcOG2fMGDRqkmJgYRUVFad++fRo3bpwyMjK0dOlSSVJWVpZbCJdkT2dlZV1yW6mpqXr22WfLfycAAAAAAChHHg3ic+fOVWJioqKioux5I0aMsL+OjY1VZGSkevToocOHD6tx48a/eFvjx4/XmDFj7GmXy6Xo6OhfvD4AAAAAADzBY0H8q6++0oYNG+wz3ZfSsWNHSdKhQ4fUuHFjRUREaNeuXW41J06ckKRL3lcuSb6+vvL19f2VXQMAAAAA4Fkeu0d8/vz5CgsLU1JS0mXr0tPTJUmRkZGSpPj4eH3yySf69ttv7Zr169crODhYLVu29FS7AAAAAAAY4ZEz4kVFRZo/f76GDh0qH5//buLw4cNatGiR+vTpozp16mjfvn0aPXq0unTpori4OElSr1691LJlS91zzz2aOnWqsrKy9OSTTyolJYUz3gAAAACAKs8jQXzDhg3KzMzUfffd5zbf6XRqw4YNevHFF5Wbm6vo6Gj1799fTz75pF3j7e2tVatW6cEHH1R8fLwCAwM1dOhQt/eOAwAAAABQVXkkiPfq1UuWZRWbHx0drffff/+Ky8fExOi9997zRGsAAAAAAFQoj75HHAAAAAAAuCOIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCr3ID5hwgQ5HA63T/Pmze3x8+fPKyUlRXXq1FHNmjXVv39/nThxwm0dmZmZSkpKUkBAgMLCwvT444+roKCgvFsFAAAAAMA4H0+stFWrVtqwYcN/N+Lz382MHj1aq1ev1j/+8Q+FhIRo5MiRuu2227R9+3ZJUmFhoZKSkhQREaEdO3bo+PHjGjJkiGrUqKHJkyd7ol0AAAAAAIzxSBD38fFRREREsfnZ2dmaO3euFi1apN/+9reSpPnz56tFixb68MMPdeONN2rdunX67LPPtGHDBoWHh6tNmzaaNGmSxo0bpwkTJsjpdHqiZQAAAAAAjPDIPeIHDx5UVFSUrr32Wg0ePFiZmZmSpL179yo/P189e/a0a5s3b64GDRooLS1NkpSWlqbY2FiFh4fbNQkJCXK5XNq/f/8lt5mXlyeXy+X2AQAAAACgsin3IN6xY0ctWLBAa9eu1axZs3TkyBF17txZZ86cUVZWlpxOp2rVquW2THh4uLKysiRJWVlZbiH84vjFsUtJTU1VSEiI/YmOji7fHQMAAAAAoByU+6XpiYmJ9tdxcXHq2LGjYmJi9Pbbb8vf37+8N2cbP368xowZY0+7XC7COAAAAACg0vH468tq1aqlpk2b6tChQ4qIiNCFCxd0+vRpt5oTJ07Y95RHREQUe4r6xemS7ju/yNfXV8HBwW4fAAAAAAAqG48H8ZycHB0+fFiRkZFq166datSooY0bN9rjGRkZyszMVHx8vCQpPj5en3zyib799lu7Zv369QoODlbLli093S4AAAAAAB5V7pemP/bYY+rbt69iYmJ07NgxPfPMM/L29tbAgQMVEhKi5ORkjRkzRqGhoQoODtZDDz2k+Ph43XjjjZKkXr16qWXLlrrnnns0depUZWVl6cknn1RKSop8fX3Lu10AAAAAAIwq9yD+zTffaODAgfrhhx9Ur1493Xzzzfrwww9Vr149SdILL7wgLy8v9e/fX3l5eUpISND//u//2st7e3tr1apVevDBBxUfH6/AwEANHTpUEydOLO9WAQAAAAAwrtyD+FtvvXXZcT8/P82cOVMzZ868ZE1MTIzee++98m4NAAAAAIAK5/F7xAEAAAAAwH8RxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAEA1kJqaqvbt2ysoKEhhYWHq16+fMjIy3Gq6desmh8Ph9nnggQfs8QULFhQbv/j59ttvTe8SAABVlk9FNwAAADzv/fffV0pKitq3b6+CggL9+c9/Vq9evfTZZ58pMDDQrhs+fLgmTpxoTwcEBNhf33nnnerdu7fbeocNG6bz588rLCzM8zsBAMBVgiAOAEA1sHbtWrfpBQsWKCwsTHv37lWXLl3s+QEBAYqIiChxHf7+/vL397env/vuO23atElz5871TNMAAFyluDQdAIBqKDs7W5IUGhrqNn/hwoWqW7eurr/+eo0fP15nz5695DreeOMNBQQE6Pbbb/dorwAAXG04Iw4AQDVTVFSkRx55RDfddJOuv/56e/6gQYMUExOjqKgo7du3T+PGjVNGRoaWLl1a4nrmzp2rQYMGuZ0lBwAAV0YQBwCgmklJSdGnn36qDz74wG3+iBEj7K9jY2MVGRmpHj166PDhw2rcuLFbbVpamg4cOKD/+7//M9IzAABXEy5NBwCgGhk5cqRWrVqlzZs3q379+pet7dixoyTp0KFDxcbmzJmjNm3aqF27dh7pEwCAq1m5B/HyeD2KJGVmZiopKUkBAQEKCwvT448/roKCgvJuFwCAasGyLI0cOVLLli3Tpk2b1KhRoysuk56eLkmKjIx0m5+Tk6O3335bycnJnmgVAICrXrlfml4er0cpLCxUUlKSIiIitGPHDh0/flxDhgxRjRo1NHny5PJuGQCAq15KSooWLVqkFStWKCgoSFlZWZKkkJAQ+fv76/Dhw1q0aJH69OmjOnXqaN++fRo9erS6dOmiuLg4t3UtWbJEBQUFuvvuuytiVwAAqPLKPYiXx+tR1q1bp88++0wbNmxQeHi42rRpo0mTJmncuHGaMGGCnE5nebcNAEC5a/jE6opuwfbVrFmSfrwq7afq9HlENWN7qsD1nb5f9bYmTJ6movzz8gmuq4Dr4pX/m7uK7UfW/02X97Ud1WbKdlPtl9rRKUkV3QIAAFfk8Ye1Xe71KG+++aYiIiLUt29fPfXUU/ZZ8bS0NMXGxio8PNyuT0hI0IMPPqj9+/erbdu2xbaTl5envLw8e9rlcnlidwAAqJJixq267LhPcD1FDJpSqnVF3DO9PFoCAKDa8mgQ/6WvR8nKynIL4ZLs6YuX0v1camqqnn32WQ/tCQAAAAAA5cOjQbw8Xo9SWuPHj9eYMWPsaZfLpejo6F/WOAAAAAAAHuKx15f9mtejRERE6MSJE241F6cvdV+5r6+vgoOD3T4AAAAAAFQ25R7Ey+P1KPHx8frkk0/07bff2jXr169XcHCwWrZsWd4tAwAAAABgTLlfml4er0fp1auXWrZsqXvuuUdTp05VVlaWnnzySaWkpMjX17e8WwYAAAAAwJhyPyM+a9YsZWdnq1u3boqMjLQ/S5YskSQ5nU5t2LBBvXr1UvPmzfXoo4+qf//+evfdd+11eHt7a9WqVfL29lZ8fLzuvvtuDRkyxO294wAAAAAAVEXlfkbcsqzLjkdHR+v999+/4npiYmL03nvvlVdbAAAAAABUCh57WBsAAAAAACiOIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAAAAAAAYRxAEAAAAAMIggDgAAAACAQQRxAAAAAAAMIogDAAAAAGAQQRwAAAAAAIMI4gAAAAAAGEQQBwAAAADAIII4AAAAAAAGEcQBAAAAADCIIA4AAAAAgEEEcQAAAAAADCKIAwAAAABgEEEcAAAAAACDCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABhHEAQAAAAAwiCAOAAAAAIBBBHEAAAAAAAwiiAMAAAAAYBBBHAAAAAAAgwjiAAAAuCqlpqaqffv2CgoKUlhYmPr166eMjAy3mqysLN1zzz2KiIhQYGCgfvOb3+idd96poI4BVBcEcQAAAFyV3n//faWkpOjDDz/U+vXrlZ+fr169eik3N9euGTJkiDIyMrRy5Up98sknuu222zRgwAB9/PHHFdg5gKudT0U3AAAAAHjC2rVr3aYXLFigsLAw7d27V126dJEk7dixQ7NmzVKHDh0kSU8++aReeOEF7d27V23btjXeM4DqgTPiAAAAqBays7MlSaGhofa8Tp06acmSJTp58qSKior01ltv6fz58+rWrVsFdQmgOiCIAwAA4KpXVFSkRx55RDfddJOuv/56e/7bb7+t/Px81alTR76+vrr//vu1bNkyNWnSpAK7Bcpm69at6tu3r6KiouRwOLR8+XJ7LD8/X+PGjVNsbKwCAwMVFRWlIUOG6NixYxXXMAjiAAAAuPqlpKTo008/1VtvveU2/6mnntLp06e1YcMG7dmzR2PGjNGAAQP0ySefVFCnQNnl5uaqdevWmjlzZrGxs2fP6qOPPtJTTz2ljz76SEuXLlVGRoZuueWWCugUF3GPOAAAAK5qI0eO1KpVq7R161bVr1/fnn/48GG98sor+vTTT9WqVStJUuvWrbVt2zbNnDlTr776akW1DJRJYmKiEhMTSxwLCQnR+vXr3ea98sor6tChgzIzM9WgQQMTLeJnCOIAAAC4KlmWpYceekjLli3Tli1b1KhRI7fxs2fPSpK8vNwvEvX29lZRUZGxPgHTsrOz5XA4VKtWrYpupdoiiAMAAOCqlJKSokWLFmnFihUKCgpSVlaWpB/PEPr7+6t58+Zq0qSJ7r//fk2fPl116tTR8uXLtX79eq1ataqCuwc84/z58xo3bpwGDhyo4ODgim6n2iKIAwAA4Bdr+MTqim7hkr6aNUuSij0BvU6fR1QztqckKb/749r7/uuK754gK/+cfGpFKrTPaP1pqyVtrZz7dnRKUkW3gCoqPz9fAwYMkGVZmvX/fz9QMQjiAAAAuCrFjLvyWe0aodeo3h/+bKAboGJdDOFfffWVNm3axNnwCkYQBwAAAICr2MUQfvDgQW3evFl16tSp6JaqPYI4AAAAAFRhOTk5OnTokD195MgRpaenKzQ0VJGRkbr99tv10UcfadWqVSosLLSflxAaGiqn01lRbVdrlTqIz5w5U9OmTVNWVpZat26tv/3tb+rQoUNFtwUAAACgGqnMz0KQpPOZ+3Ri8X9vsRgzZowkKfD6Hqp18yD9Z+VKSVKbNm3clgsfOFl+DeKM9VkWV/uzECptEF+yZInGjBmjV199VR07dtSLL76ohIQEZWRkKCwsrKLbAwAAAIBKwa9B3GWfiVCa5yXArEobxGfMmKHhw4fr3nvvlSS9+uqrWr16tebNm6cnnniiWH1eXp7y8vLs6ezsbEmSy+Uy03A5Kso7W9EtVDtV8Tip6jjOzeM4N4/j3DyOc/M4zs3jODeP49y8qnqcX+zbsqzL1jmsK1VUgAsXLiggIED//Oc/1a9fP3v+0KFDdfr0aa1YsaLYMhMmTNCzzz5rsEsAAAAAAIr7+uuvVb9+/UuOV8oz4t9//70KCwsVHh7uNj88PFyff/55icuMHz/evhdCkoqKinTy5EnVqVNHDofDo/3iRy6XS9HR0fr66695HQKuWhznqA44zlEdcJyjOuA4N8+yLJ05c0ZRUVGXrauUQfyX8PX1la+vr9u8WrVqVUwz1VxwcDC/6LjqcZyjOuA4R3XAcY7qgOPcrJCQkCvWeBnoo8zq1q0rb29vnThxwm3+iRMnFBERUUFdAQAAAADw61XKIO50OtWuXTtt3LjRnldUVKSNGzcqPj6+AjsDAAAAAODXqbSXpo8ZM0ZDhw7VDTfcoA4dOujFF19Ubm6u/RR1VD6+vr565plnit0iAFxNOM5RHXCcozrgOEd1wHFeeVXKp6Zf9Morr2jatGnKyspSmzZt9PLLL6tjx44V3RYAAAAAAL9YpQ7iAAAAAABcbSrlPeIAAAAAAFytCOIAAAAAABhEEAcAAAAAwCCCOAAAAAAABlXa15cBQEV6+OGH9d1335W6vnHjxpo0aZIHOwLKX35+vsryzFYvLy/5+PBPBwAAfi2emo4yW7x4sc6cOVPq+rCwMPXr189zDQEe0Lp1a61cubJUtZZlacCAAdq1a5eHuwLKV9OmTVW/fv0rhnGHwyHLspSbm8txjiqnf//+On78eKnrW7ZsqTlz5niwI6D8cZxXPfxZG2X23HPPaezYsaU+izJ58mSCOKocLy8vxcTElLqev2miKgoMDNSmTZtKXd++fXsPdgN4xpdffqmPP/641PUdOnTwYDeAZ3CcVz0EcZRZjRo1NGTIkFLXv/LKKx7sBvAMh8Ph0XqgMuA4R3XAcYvqgOO86uFhbSgz/uEGAAAAAL8cQRwAAAAAAIO4NB0ASnDu3DlNnDixVLXcHw4AAICyIIijzPLz87V169ZS1VqWRUhBlTR79mydO3eu1PUJCQke7AbwDKfTqU6dOpW6vm7duh7sBvCM3Nxc3XfffaWq5d8tqKo4zqsegjjK7J577tGaNWtKXT9s2DDPNQN4SJcuXSq6BcDjOnTooO+++67U9U2aNPFgN4BnrFmzRvn5+aWu9/f392A3gGdwnFc9vEccZZafn1+mv6J5eXnJx4e/+QBAZdOmTRutXLmy1P9Nv+OOO3iPOKqcxYsX68yZM6WuDwsL47WrqHI4zqsegjjKrGnTpqpfv36pai3L0tmzZ7Vz504PdwUAKKu2bduW6b2z7du31+7duz3YEVD+rr/+eo0dO7bUf3CaOXMmf3BClcNxXvVwmhJlFhgYqE2bNpW6vn379h7sBgDwS/E6SlQHNWrU0JAhQ0pd/8orr3iwG8AzOM6rHl5fhjLjH24AAKCq4N8tqA44zqsegjgAAAAAAAZxaToAANXUuXPnNHHixFLV8kgZAADKD0EcAIBqavbs2Tp37lyp6xMSEjzYDeAZ+fn52rp1a6lqeb8yqiqO86qHII4yczqd6tSpU6nr69at68FuAAC/VJcuXSq6BcDj7rnnHq1Zs6bU9cOGDfNcM4CHcJxXPby+DGU2atQofffdd6Wub9KkiSZNmuTBjgAAAEqWn59fprN/Xl5e8vHhXBWqFo7zqocgjjJr06aNVq5cWepf9jvuuIP3FAIAgArRtGlT1a9fv1S1lmXp7Nmz2rlzp4e7AsoXx3nVw59BUGYOh0MNGjQodT1/6wEAABUlMDBQmzZtKnV9+/btPdgN4Bkc51UPry9DmfGeQgAAUFXw7xZUBxznVQ9BHAAAAAAAgwjiAAAAAAAYxD3iKLNz585p4sSJparl/nAAAAAAcEcQR5nNnj1b586dK3V9QkKCB7sBAAC4NKfTqU6dOpW6vm7duh7sBvAMjvOqhyCOMuvSpUtFtwAAAFAqHTp00HfffVfq+iZNmniwG8AzOM6rHt4jDgAAgKtWmzZttHLlylLfLnfHHXdo165dHu4KKF8c51UPZ8QBAABw1XI4HGrQoEGp6zlHhaqI47zq4anpAAAAuGrxfmVUBxznVQ9BHAAAAAAAgwjiAAAAAAAYxD3iAAAAuGqdO3dOEydOLFUt982iquI4r3p4ajoAAACuWlu3btW5c+dKXR8SEqIbb7zRgx0B5Y/jvOohiAMAAAAAYBD3iAMAAAAAYBBBHAAAAAAAgwjiAAAAAAAYRBAHAAAAAMAggjgAGNStWzc98sgjFd3GJTVs2FAvvvhilVlveXI4HFq+fHlFt+EREyZMUJs2bcp1nUePHpXD4VB6enq5rrcqWbBggWrVquXRbXjiZ1eSq/n4B4DKiCAOAAYtXbpUkyZNKlVtVQ86r7/+um6++WZJ0u7duzVixIhSL7tlyxY5HA6dPn3aQ915xt///nd17txZtWvXVu3atdWzZ0/t2rWr1MsPGzZMDofD7dO7d+/LLrNgwYJiy1z8fPvtt792lzyutH+cOn/+vIYNG6bY2Fj5+PioX79+Hu+tOjl+/LgSExNLXV+WP0J069at2LH5wAMPlLjOuLg4+fn5KSwsTCkpKfbYli1bdOuttyoyMlKBgYFq06aNFi5cWOp+AaCy8anoBgCgOgkNDa2Q7ebn56tGjRpGt7lixQrdcsstkqR69eoZ3fZFlmWpsLBQPj5m/ne3ZcsWDRw4UJ06dZKfn5+ef/559erVS/v379c111xTqnX07t1b8+fPt6d9fX0vW3/nnXcWC+vDhg3T+fPnFRYWVvadqKQKCwvl7++vUaNG6Z133qnodq46ERERHl3/8OHDNXHiRHs6ICDAbXzGjBn661//qmnTpqljx47Kzc3V0aNH7fEdO3YoLi5O48aNU3h4uFatWqUhQ4YoJCREv//97z3aOwB4AmfEAcCgn579a9iwoSZPnqz77rtPQUFBatCggV577TW7tlGjRpKktm3byuFwqFu3bvbYnDlz1KJFC/n5+al58+b63//9X3vs4pn0JUuWqGvXrvLz89PChQs1bNgw9evXT9OnT1dkZKTq1KmjlJQU5efnX7Jfh8Oh2bNn6/e//70CAgLUokULpaWl6dChQ+rWrZsCAwPVqVMnHT582G258+fPa926dXYQ//ml6Q6HQ3PmzNEf/vAHBQQE6LrrrtPKlSvt/rt37y5Jql27thwOh4YNGyZJKioqUmpqqho1aiR/f3+1bt1a//znP+31XjyTvmbNGrVr106+vr764IMP1K1bN40aNUpjx45VaGioIiIiNGHChEvu98Xv4dtvv63OnTvL399f7du31xdffKHdu3frhhtuUM2aNZWYmKjvvvvOXm7hwoX605/+pDZt2qh58+aaM2eOioqKtHHjxktu6+d8fX0VERFhf2rXrn3Zen9/f7d6b29vbdq0ScnJycVqZ8+erejoaAUEBGjAgAHKzs6+7LqLioo0depUNWnSRL6+vmrQoIGee+45t5ovv/xS3bt3V0BAgFq3bq20tDR77IcfftDAgQN1zTXXKCAgQLGxsVq8eLE9PmzYML3//vt66aWX7DOlPw1fPxUYGKhZs2Zp+PDhlwyNFy/jnjdvnho0aKCaNWvqT3/6kwoLCzV16lRFREQoLCys2D5czunTp3X//fcrPDxcfn5+uv7667Vq1Sq3mn/9619q0aKFatasqd69e+v48eNu45f7fZWkb775RgMHDlRoaKgCAwN1ww03aOfOnSX2c/jwYV177bUaOXKkLMuyz0wvX75c1113nfz8/JSQkKCvv/7abblZs2apcePGcjqdatasmf7v//7Pbfynl6ZfPP6XLl1a4s92y5Ytuvfee5WdnW3/3C73+yT9GLx/epwGBwfbY6dOndKTTz6pN954Q4MGDVLjxo0VFxdn//dDkv785z9r0qRJ6tSpkxo3bqyHH35YvXv31tKlSy+7XQCotCwAgDFdu3a1Hn74YcuyLCsmJsYKDQ21Zs6caR08eNBKTU21vLy8rM8//9yyLMvatWuXJcnasGGDdfz4ceuHH36wLMuy3nzzTSsyMtJ65513rC+//NJ65513rNDQUGvBggWWZVnWkSNHLElWw4YN7Zpjx45ZQ4cOtYKDg60HHnjAOnDggPXuu+9aAQEB1muvvWb3FxMTY73wwgv2tCTrmmuusZYsWWJlZGRY/fr1sxo2bGj99re/tdauXWt99tln1o033mj17t3bbT9XrVplNW3a9LLrrV+/vrVo0SLr4MGD1qhRo6yaNWtaP/zwg1VQUGC98847liQrIyPDOn78uHX69GnLsizrL3/5i9W8eXNr7dq11uHDh6358+dbvr6+1pYtWyzLsqzNmzdbkqy4uDhr3bp11qFDh6wffvjB6tq1qxUcHGxNmDDB+uKLL6zXX3/dcjgc1rp169x6WrZsmdv38OK2Lu5nu3btrG7dulkffPCB9dFHH1lNmjSxHnjggUv+vF0ul+Xn52e9++67pTk8rKFDh1ohISFWvXr1rKZNm1oPPPCA9f3335dq2YumT59uhYSEWGfPnrXnPfPMM1ZgYKD129/+1vr444+t999/32rSpIk1aNCgy65r7NixVu3ata0FCxZYhw4dsrZt22b9/e9/tyzL/Xu0atUqKyMjw7r99tutmJgYKz8/37Isy/rmm2+sadOmWR9//LF1+PBh6+WXX7a8vb2tnTt3WpZlWadPn7bi4+Ot4cOHW8ePH7eOHz9uFRQUlOr7dOuttxab/8wzz1g1a9a0br/9dmv//v3WypUrLafTaSUkJFgPPfSQ9fnnn1vz5s2zJFkffvjhFbdTWFho3XjjjVarVq2sdevWWYcPH7beffdd67333rMsy7Lmz59v1ahRw+rZs6e1e/dua+/evVaLFi3cvq9X+n09c+aMde2111qdO3e2tm3bZh08eNBasmSJtWPHDnufWrdubVmWZf373/+2IiIirP/5n/+x13+xhxtuuMHasWOHtWfPHqtDhw5Wp06d7JqlS5daNWrUsGbOnGllZGRYf/3rXy1vb29r06ZNds2ljv+SfrZ5eXnWiy++aAUHB9s/tzNnzlzy+9i1a1erbt26Vp06daxWrVpZTzzxhJWbm2uPL1myxPL19bVef/11q3nz5tY111xj3XHHHVZmZuZlfz433XST9eijj162BgAqK4I4ABj08yB+991322NFRUVWWFiYNWvWLMuy/vuP4Y8//thtHY0bN7YWLVrkNm/SpElWfHy823IvvviiW83QoUOtmJgYt6Bzxx13WHfeeac9XVJgfvLJJ+3ptLQ0S5I1d+5ce97ixYstPz8/t20NHz7ceuyxx0q93pycHEuStWbNGsuy/huoT506ZdecP3/eCggIsAPKRcnJydbAgQPdllu+fLlbTdeuXa2bb77ZbV779u2tcePGufX08yAyZ84ct/2UZG3cuNGel5qaajVr1sy6lAcffNC69tprrXPnzl2y5qcWL15srVixwtq3b5+1bNkyq0WLFlb79u1LFU4vatGihfXggw+6zXvmmWcsb29v65tvvrHnrVmzxvLy8rKOHz9e4npcLpfl6+trB++fK+l7tH//fkuSdeDAgUv2l5SU5Baefvo7UVqXC+IBAQGWy+Wy5yUkJFgNGza0CgsL7XnNmjWzUlNTr7idf/3rX5aXl5eVkZFR4vj8+fMtSdahQ4fseTNnzrTCw8Pt6Sv9vs6ePdsKCgqy/9BW0j61bt3a2r59u1W7dm1r+vTpJfbw0z8sHDhwwJJk/8GjU6dO1vDhw92Wu+OOO6w+ffrY01c6/n/+s50/f74VEhJSYs8/N3v2bGvt2rXWvn37rDfffNO65pprrD/84Q/2eGpqqlWjRg2rWbNm1tq1a620tDSrR48eVrNmzay8vLwS17lkyRLL6XRan376aal6AIDKhnvEAaACxcXF2V87HA5FRERc9gFbubm5Onz4sJKTkzV8+HB7fkFBgUJCQtxqb7jhhmLLt2rVSt7e3vZ0ZGSkPvnkk1L3GB4eLkmKjY11m3f+/Hm5XC4FBwfLsiy9++67evvtt0u93sDAQAUHB1923w8dOqSzZ8/qd7/7ndv8CxcuqG3btm7zStr3n25P+nHfr/Qws9Ls+6XWMWXKFL311lvasmWL/Pz8Lrudi+666y7769jYWMXFxalx48basmWLevToocTERG3btk2SFBMTo/3797stn5aWpgMHDhS77FiSGjRo4Hafenx8vIqKipSRkaGDBw+6Pahr9uzZuu6665SXl6cePXpctueffo8iIyMlSd9++62aN2+uwsJCTZ48WW+//bb+85//6MKFC8rLyyt2f/DPtWrVSl999ZUkqXPnzlqzZs1l63+qYcOGCgoKsqfDw8Pl7e0tLy8vt3mleZBdenq66tevr6ZNm16yJiAgQI0bN7anf3pcleb3NT09XW3btr3s8yMyMzP1u9/9Ts8991yJD7bz8fFR+/bt7enmzZurVq1aOnDggDp06KADBw4Ue1jiTTfdpJdeeumy+3+5n21JJk+erMmTJ9vTn332mRo0aOC27djYWEVGRqpHjx46fPiwGjdurKKiIuXn5+vll19Wr169JEmLFy9WRESENm/erISEBLftbN68Wffee6/+/ve/q1WrVpfdBwCorAjiAFCBfv4ANYfDoaKiokvW5+TkSPrx6dwdO3Z0G/tpwJZ+DLe/dns/X8bhcFxy3sX17Nq1SwUFBerUqVOp11uaXi7u++rVq4s9+OznDzQzue8lrWP69OmaMmWKNmzYUOwPAGVx7bXXqm7dujp06JB69OihOXPm6Ny5cyXuj/Tjvcht2rRRu3btyrSdG264we3p/OHh4Ze8V/vnLncsTJs2TS+99JJefPFFxcbGKjAwUI888oguXLhw2XW+99579rML/P39y7AnJf+cf8nPvrTbLmndlmVJKt3va2m2Ua9ePUVFRWnx4sW677773O6v9qTL/WxL8sADD2jAgAH2dFRUVIl1F78Xhw4dUuPGje2Q37JlS7umXr16qlu3rjIzM92Wff/999W3b1+98MILGjJkSBn3CAAqD4I4AFRSTqdT0o9Pi74oPDxcUVFR+vLLLzV48OCKau2yVqxYoaSkpGJ/GCiLkva9ZcuW8vX1VWZmprp27fqr+/SUqVOn6rnnntO//vWvEs/Ml8U333yjH374wQ4ql3vyek5Ojt5++22lpqaWOJ6Zmaljx47Z4ejDDz+Ul5eXmjVrJn9/fzVp0sSt/rrrrpO/v782btyoP/7xj7+o/+3bt+vWW2/V3XffLenHEPfFF1+4BS6n0+n2c5Z+PNtfGcTFxembb77RF198cdmz4pdSmt/XuLg4zZkzRydPnrzkWXF/f3+tWrVKffr0UUJCgtatW+d21r+goEB79uxRhw4dJEkZGRk6ffq0WrRoIUlq0aKFtm/frqFDh9rLbN++3e3nUFYl/dxCQ0NL9WaIi3/0uXhc33TTTXbf9evXlySdPHlS33//vduxsGXLFv3+97/X888/X6bXIQJAZUQQB4BKKiwsTP7+/lq7dq3q168vPz8/hYSE6Nlnn9WoUaMUEhKi3r17Ky8vT3v27NGpU6c0ZsyYim5bK1eudHtN0S8RExMjh8Nhhw9/f38FBQXpscce0+jRo1VUVKSbb75Z2dnZ2r59u4KDg91CRkV5/vnn9fTTT2vRokVq2LChsrKyJEk1a9ZUzZo1L7tsTk6Onn32WfXv318RERE6fPiwxo4dqyZNmhS7NLckS5YsUUFBgR16f87Pz09Dhw7V9OnT5XK5NGrUKA0YMOCSTyD38/PTuHHjNHbsWDmdTt1000367rvvtH///hKfyF6S6667Tv/85z+1Y8cO1a5dWzNmzNCJEyfcAmDDhg21c+dOHT16VDVr1lRoaKjbZeQ/9dlnn+nChQs6efKkzpw5Ywe6Nm3alKqfsuratau6dOmi/v37a8aMGWrSpIk+//zzUr3f/aIr/b4OHDhQkydPVr9+/ZSamqrIyEh9/PHHioqKUnx8vL2ewMBArV69WomJiUpMTNTatWvtY6pGjRp66KGH9PLLL8vHx0cjR47UjTfeaAfzxx9/XAMGDFDbtm3Vs2dPvfvuu1q6dKk2bNjwi783DRs2VE5OjjZu3KjWrVsrICCgxFsODh8+rEWLFqlPnz6qU6eO9u3bp9GjR6tLly721SJNmzbVrbfeqocfflivvfaagoODNX78eDVv3tx+g8LmzZv1+9//Xg8//LD69+9v/245nc4Key0kAPwavL4MACopHx8fvfzyy5o9e7aioqJ06623SpL++Mc/as6cOZo/f75iY2PVtWtXLViwwH7dWUU6fPiwDh06VKrgeDnXXHONnn32WT3xxBMKDw/XyJEjJUmTJk3SU089pdTUVLVo0UK9e/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size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 26159 (\\N{CJK UNIFIED IDEOGRAPH-662F}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 19981 (\\N{CJK UNIFIED IDEOGRAPH-4E0D}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from font(s) 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found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-1124 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-1124\n","是       1069\n","不是       966\n","不重要      946\n","回答正确      10\n","问法错误       9\n","Name: count, dtype: int64\n"]},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 19981 (\\N{CJK UNIFIED IDEOGRAPH-4E0D}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 26159 (\\N{CJK UNIFIED IDEOGRAPH-662F}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 35201 (\\N{CJK UNIFIED IDEOGRAPH-8981}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 22238 (\\N{CJK UNIFIED IDEOGRAPH-56DE}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 31572 (\\N{CJK UNIFIED IDEOGRAPH-7B54}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 27491 (\\N{CJK UNIFIED IDEOGRAPH-6B63}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 30830 (\\N{CJK UNIFIED IDEOGRAPH-786E}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 38382 (\\N{CJK UNIFIED IDEOGRAPH-95EE}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 27861 (\\N{CJK UNIFIED IDEOGRAPH-6CD5}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 38169 (\\N{CJK UNIFIED IDEOGRAPH-9519}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 35823 (\\N{CJK UNIFIED IDEOGRAPH-8BEF}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-1686 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-1686\n","不是      1581\n","是        999\n","不重要      383\n","回答正确      24\n","问法错误      13\n","Name: count, dtype: int64\n"]},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA+IAAAIgCAYAAAABTdNAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAABQYElEQVR4nO3df3xP9f//8ftm9sPYL2yzzI+Sn/kVYuRXlmFv8U6kvDUlyhsl5dfnHSnVkLekRD/R+4169y4/y7L8LGZYFknzI6LYJLaXDbPZ8/tHX+fdK8PGXmdmt+vl8rpcnHMe55zH2es5l91f57zOcTPGGAEAAAAAAFu4F3cDAAAAAACUJgRxAAAAAABsRBAHAAAAAMBGBHEAAAAAAGxEEAcAAAAAwEYEcQAAAAAAbEQQBwAAAADARh7F3YCr5OXl6ciRI6pQoYLc3NyKux0AAAAAwA3OGKNTp04pLCxM7u6XPu99wwbxI0eOKDw8vLjbAAAAAACUMocPH1bVqlUvufyGDeIVKlSQ9PsPwM/Pr5i7AQAAAADc6BwOh8LDw608eik3bBC/cDm6n58fQRwAAAAAYJsrfT2am7UBAAAAAGAjgjgAAAAAADYiiAMAAAAAYCOCOAAAAAAANiKIAwAAAABgI4I4AAAAAAA2IogDAAAAAGAjgjgAAAAAADYiiAMAAAAAYCOCOAAAAAAANip0EN+wYYO6d++usLAwubm5acmSJRfV7N69W/fcc4/8/f3l6+urFi1a6NChQ9bys2fPaujQoapYsaLKly+vXr16KS0tzWkbhw4dUnR0tMqVK6fg4GCNGjVKubm5hT9CFMqV3t8BAwbIzc3N6dWlSxenmj179qhHjx6qVKmS/Pz8dOedd2rt2rVONU888YSaNWsmLy8vNWnSxMVHBQAAAADXj0IH8aysLDVu3FizZs3Kd/n+/ft15513qm7dulq3bp127Nih8ePHy9vb26p56qmntHz5cn388cdav369jhw5onvvvddafv78eUVHR+vcuXPatGmT5s+fr3nz5mnChAlXcYgojCu9v5LUpUsXHT161HotWrTIaflf/vIX5ebmas2aNUpKSlLjxo31l7/8RampqU51jzzyiO6//36XHAcAAAAAXK/cjDHmqld2c9PixYvVs2dPa17fvn1VtmxZ/etf/8p3nYyMDFWuXFkLFy7UfffdJ0n64YcfVK9ePSUkJKhVq1ZauXKl/vKXv+jIkSMKCQmRJM2ZM0djxozRr7/+Kk9Pzyv25nA45O/vr4yMDPn5+V3tIZZq+b2/AwYMUHp6er5XQkjS8ePHVblyZW3YsEFt27aVJJ06dUp+fn6Kj49XZGSkU/3EiRO1ZMkSJScnu+goAAAAAMAeBc2hRfod8by8PH322WeqXbu2oqKiFBwcrJYtWzqFtqSkJOXk5DgFsrp166patWpKSEiQJCUkJKhhw4ZWCJekqKgoORwO7dq1K999Z2dny+FwOL3gGuvWrVNwcLDq1KmjIUOG6LfffrOWVaxYUXXq1NEHH3ygrKws5ebm6q233lJwcLCaNWtWjF0DAAAAwPWhSIP4sWPHlJmZqcmTJ6tLly5atWqV/vrXv+ree+/V+vXrJUmpqany9PRUQECA07ohISHWpcupqalOIfzC8gvL8hMbGyt/f3/rFR4eXpSHhv+vS5cu+uCDD7R69WpNmTJF69evV9euXXX+/HlJv59F//LLL7V9+3ZVqFBB3t7emj59uuLi4hQYGFjM3QMAAABA8fMoyo3l5eVJknr06KGnnnpKktSkSRNt2rRJc+bMUfv27Ytyd07GjRunkSNHWtMOh4Mw7gJ9+/a1/t2wYUM1atRIt9xyi9atW6dOnTrJGKOhQ4cqODhYX331lXx8fPTuu++qe/fu2rp1q6pUqVKM3QMAAABA8SvSM+KVKlWSh4eH6tev7zS/Xr161l3TQ0NDde7cOaWnpzvVpKWlKTQ01Kr5813UL0xfqPkzLy8v+fn5Ob3gejfffLMqVaqkffv2SZLWrFmjFStW6MMPP1SbNm10++23680335SPj4/mz59fzN0CAAAAQPEr0iDu6empFi1aKCUlxWn+nj17VL16dUlSs2bNVLZsWa1evdpanpKSokOHDikiIkKSFBERoZ07d+rYsWNWTXx8vPz8/C4K+SheP//8s3777TfrTPfp06clSe7uzkPL3d3dumICAAAAAEqzQl+anpmZaZ39lKQDBw4oOTlZQUFBqlatmkaNGqX7779f7dq1U8eOHRUXF6fly5dr3bp1kiR/f38NHDhQI0eOVFBQkPz8/DR8+HBFRESoVatWkqTOnTurfv366t+/v6ZOnarU1FQ9++yzGjp0qLy8vIrmyJGvy72/QUFBev7559WrVy+FhoZq//79Gj16tGrVqqWoqChJv3+IEhgYqJiYGE2YMEE+Pj565513dODAAUVHR1vb3bdvnzIzM5WamqozZ85Yd02vX79+ge6KDwAAAAAlVaEfX7Zu3Tp17NjxovkxMTGaN2+eJOn9999XbGysfv75Z9WpU0fPP/+8evToYdWePXtWTz/9tBYtWqTs7GxFRUXpzTffdLrs/KefftKQIUO0bt06+fr6KiYmRpMnT5aHR8E+OyjJjy+rMfazYtv32UM7lLbo/y6a73tbJwV1/rt+/fRFnTv2o/LOZqlM+SD51GyqgLZ/Uxnf/92ILfvoXqVv+EDnUvfJ5OWqbKVqCmj9gHxuaW7VpC4cq+zD3120n5sef08e/iEXzXe1g5Ojr1wEAAAAAJdR0Bx6Tc8Rv54RxFEYBHEAAAAA16pYniMOAAAAAAAujyAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANio0EF8w4YN6t69u8LCwuTm5qYlS5Zcsvbxxx+Xm5ubZsyY4TT/xIkT6tevn/z8/BQQEKCBAwcqMzPTqWbHjh1q27atvL29FR4erqlTpxa2VQAAAAAArjuFDuJZWVlq3LixZs2addm6xYsXa/PmzQoLC7toWb9+/bRr1y7Fx8drxYoV2rBhgwYPHmwtdzgc6ty5s6pXr66kpCS98sormjhxot5+++3CtgsAAAAAwHXFo7ArdO3aVV27dr1szS+//KLhw4friy++UHR0tNOy3bt3Ky4uTlu3blXz5s0lSa+//rq6deumadOmKSwsTAsWLNC5c+f0/vvvy9PTUw0aNFBycrKmT5/uFNj/KDs7W9nZ2da0w+Eo7KEBAAAAAOByRf4d8by8PPXv31+jRo1SgwYNLlqekJCggIAAK4RLUmRkpNzd3ZWYmGjVtGvXTp6enlZNVFSUUlJSdPLkyXz3GxsbK39/f+sVHh5exEcGAAAAAMC1K/IgPmXKFHl4eOiJJ57Id3lqaqqCg4Od5nl4eCgoKEipqalWTUhIiFPNhekLNX82btw4ZWRkWK/Dhw9f66EAAAAAAFDkCn1p+uUkJSXptdde0zfffCM3N7ei3PQVeXl5ycvLy9Z9AgAAAABQWEV6Rvyrr77SsWPHVK1aNXl4eMjDw0M//fSTnn76adWoUUOSFBoaqmPHjjmtl5ubqxMnTig0NNSqSUtLc6q5MH2hBgAAAACAkqhIg3j//v21Y8cOJScnW6+wsDCNGjVKX3zxhSQpIiJC6enpSkpKstZbs2aN8vLy1LJlS6tmw4YNysnJsWri4+NVp04dBQYGFmXLAAAAAADYqtCXpmdmZmrfvn3W9IEDB5ScnKygoCBVq1ZNFStWdKovW7asQkNDVadOHUlSvXr11KVLFw0aNEhz5sxRTk6Ohg0bpr59+1qPOnvwwQf1/PPPa+DAgRozZoy+++47vfbaa3r11Vev5VgBAAAAACh2hQ7i27ZtU8eOHa3pkSNHSpJiYmI0b968Am1jwYIFGjZsmDp16iR3d3f16tVLM2fOtJb7+/tr1apVGjp0qJo1a6ZKlSppwoQJl3x0GQAAAAAAJYWbMcYUdxOu4HA45O/vr4yMDPn5+RV3O4VSY+xnxd1CqXNwcvSViwAAAADgMgqaQ4v88WUAAAAAAODSCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0KHcQ3bNig7t27KywsTG5ublqyZIm1LCcnR2PGjFHDhg3l6+ursLAwPfTQQzpy5IjTNk6cOKF+/frJz89PAQEBGjhwoDIzM51qduzYobZt28rb21vh4eGaOnXq1R0hAAAAAADXkUIH8aysLDVu3FizZs26aNnp06f1zTffaPz48frmm2/06aefKiUlRffcc49TXb9+/bRr1y7Fx8drxYoV2rBhgwYPHmwtdzgc6ty5s6pXr66kpCS98sormjhxot5+++2rOEQAAAAAAK4fbsYYc9Uru7lp8eLF6tmz5yVrtm7dqjvuuEM//fSTqlWrpt27d6t+/fraunWrmjdvLkmKi4tTt27d9PPPPyssLEyzZ8/WP/7xD6WmpsrT01OSNHbsWC1ZskQ//PBDvvvJzs5Wdna2Ne1wOBQeHq6MjAz5+fld7SEWixpjPyvuFkqdg5Oji7sFAAAAACWcw+GQv7//FXOoy78jnpGRITc3NwUEBEiSEhISFBAQYIVwSYqMjJS7u7sSExOtmnbt2lkhXJKioqKUkpKikydP5ruf2NhY+fv7W6/w8HDXHRQAAAAAAFfJpUH87NmzGjNmjB544AHr04DU1FQFBwc71Xl4eCgoKEipqalWTUhIiFPNhekLNX82btw4ZWRkWK/Dhw8X9eEAAAAAAHDNPFy14ZycHPXp00fGGM2ePdtVu7F4eXnJy8vL5fsBAAAAAOBauCSIXwjhP/30k9asWeN0bXxoaKiOHTvmVJ+bm6sTJ04oNDTUqklLS3OquTB9oQYAAAAAgJKoyC9NvxDC9+7dqy+//FIVK1Z0Wh4REaH09HQlJSVZ89asWaO8vDy1bNnSqtmwYYNycnKsmvj4eNWpU0eBgYFF3TIAAAAAALYpdBDPzMxUcnKykpOTJUkHDhxQcnKyDh06pJycHN13333atm2bFixYoPPnzys1NVWpqak6d+6cJKlevXrq0qWLBg0apC1btmjjxo0aNmyY+vbtq7CwMEnSgw8+KE9PTw0cOFC7du3SRx99pNdee00jR44suiMHAAAAAKAYFPrxZevWrVPHjh0vmh8TE6OJEyeqZs2a+a63du1adejQQZJ04sQJDRs2TMuXL5e7u7t69eqlmTNnqnz58lb9jh07NHToUG3dulWVKlXS8OHDNWbMmAL3WdDbxl+PeHyZ/Xh8GQAAAIBrVdAcek3PEb+eEcRRGARxAAAAANfqunmOOAAAAAAA+B+COAAAAAAANiKIAwAAAABgI4I4AAAAAAA2IogDAAAAAGAjgjgAAAAAADYiiAMAAAAAYCOCOAAAAAAANiKIAwAAAABgI4I4AAAAAAA2IogDAAAAAGAjgjgAAAAAADYiiAMAAAAAYCOCOAAAAAAANiKIAwAAAABgI4I4AAAAAAA2IogDAAAAAGAjgjgAAAAAADYiiAMAAAAAYCOCOAAAAAAANiKIAwAAAABgI4I4AAAAAAA2IogDAAAAAGAjgjgAAAAAADYiiAMAAAAAYCOCOAAAAAAANiKIAwAAAABgI4I4AAAAAAA2IogDAAAAAGAjgjgAAAAAADYiiAMAAAAAYCOCOAAAAAAANiKIAwAAAABgI4I4AAAAAAA2IogDAAAAAGAjgjgAAAAAADYiiAMAAAAAYCOCOAAAAAAANiKIAwAAAABgI4I4AEg6deqURowYoerVq8vHx0etW7fW1q1breVpaWkaMGCAwsLCVK5cOXXp0kV79+512sb+/fv117/+VZUrV5afn5/69OmjtLQ0uw8FAAAA1zmCOABIevTRRxUfH69//etf2rlzpzp37qzIyEj98ssvMsaoZ8+e+vHHH7V06VJt375d1atXV2RkpLKysiRJWVlZ6ty5s9zc3LRmzRpt3LhR586dU/fu3ZWXl1fMRwcAAIDriZsxxhR3E67gcDjk7++vjIwM+fn5FXc7hVJj7GfF3UKpc3BydHG3gGJ05swZVahQQUuXLlV09P/GQrNmzdS1a1c99NBDqlOnjr777js1aNBAkpSXl6fQ0FC9/PLLevTRR7Vq1Sp17dpVJ0+etP7PycjIUGBgoFatWqXIyMhiOTYAAADYp6A5lDPiAEq93NxcnT9/Xt7e3k7zfXx89PXXXys7O1uSnJa7u7vLy8tLX3/9tSQpOztbbm5u8vLysmq8vb3l7u5u1QAAAAASQRwAVKFCBUVERGjSpEk6cuSIzp8/r3//+99KSEjQ0aNHVbduXVWrVk3jxo3TyZMnde7cOU2ZMkU///yzjh49Kklq1aqVfH19NWbMGJ0+fVpZWVl65plndP78easGAAAAkK4iiG/YsEHdu3dXWFiY3NzctGTJEqflxhhNmDBBVapUkY+PjyIjIy+6odGJEyfUr18/+fn5KSAgQAMHDlRmZqZTzY4dO9S2bVt5e3srPDxcU6dOLfzRAUAB/etf/5IxRjfddJO8vLw0c+ZMPfDAA3J3d1fZsmX16aefas+ePQoKClK5cuW0du1ade3aVe7uv/83WrlyZX388cdavny5ypcvL39/f6Wnp+v222+3agAAAADpKoJ4VlaWGjdurFmzZuW7fOrUqZo5c6bmzJmjxMRE+fr6KioqSmfPnrVq+vXrp127dik+Pl4rVqzQhg0bNHjwYGu5w+FQ586dVb16dSUlJemVV17RxIkT9fbbb1/FIQLAld1yyy1av369MjMzdfjwYW3ZskU5OTm6+eabJf3+ffHk5GSlp6fr6NGjiouL02+//WYtl6TOnTtr//79OnbsmI4fP65//etf+uWXX5xqAAAAAI/CrtC1a1d17do132XGGM2YMUPPPvusevToIUn64IMPFBISoiVLlqhv377avXu34uLitHXrVjVv3lyS9Prrr6tbt26aNm2awsLCtGDBAp07d07vv/++PD091aBBAyUnJ2v69OlOgR0Aipqvr698fX118uRJffHFFxddjePv7y9J2rt3r7Zt26ZJkyZdtI1KlSpJktasWaNjx47pnnvucX3jAAAAKDGK9HrJAwcOKDU11enuwP7+/mrZsqUSEhIkSQkJCQoICLBCuCRFRkbK3d1diYmJVk27du3k6elp1URFRSklJUUnT57Md9/Z2dlyOBxOLwAoqC+++EJxcXE6cOCA4uPj1bFjR9WtW1cPP/ywJOnjjz/WunXrrEeY3X333erZs6c6d+5sbWPu3LnavHmz9u/fr3//+9/q3bu3nnrqKdWpU6e4DgsAAADXoUKfEb+c1NRUSVJISIjT/JCQEGtZamqqgoODnZvw8FBQUJBTTc2aNS/axoVlgYGBF+07NjZWzz//fNEcCACXu94e05e1+yulb5iv3FPHVca7gsrVaa2AiId06/hVkiTHti/l2PKpzmelq0z5QJVvcJe23dzX6ThOrvtcmd+NVN6ZTHn4B6tCk7/qvx4d9cl1cqw8pg8AAOD6UKRBvDiNGzdOI0eOtKYdDofCw8OLsSMAJYlvvbbyrdf2ksv9mt8jv+aXv8Q8sMMABXYYUMSdAQAA4EZTpJemh4aGSpLS0tKc5qelpVnLQkNDdezYMaflubm5OnHihFNNftv44z7+zMvLS35+fk4vAAAAAACuN0UaxGvWrKnQ0FCtXr3amudwOJSYmKiIiAhJUkREhNLT05WUlGTVrFmzRnl5eWrZsqVVs2HDBuXk5Fg18fHxqlOnTr6XpQMAAAAAUFIUOohnZmYqOTlZycnJkn6/QVtycrIOHTokNzc3jRgxQi+++KKWLVumnTt36qGHHlJYWJh69uwpSapXr566dOmiQYMGacuWLdq4caOGDRumvn37KiwsTJL04IMPytPTUwMHDtSuXbv00Ucf6bXXXnO69BwAAAAAgJKo0N8R37Ztmzp27GhNXwjHMTExmjdvnkaPHq2srCwNHjxY6enpuvPOOxUXFydvb29rnQULFmjYsGHq1KmT3N3d1atXL82cOdNa7u/vr1WrVmno0KFq1qyZKlWqpAkTJvDoMgAAAABAiedmjDHF3YQrOBwO+fv7KyMjo8R9X/x6u5t0acDdpO3HOLcf4xwAAMC1CppDi/Q74gAAAAAA4PII4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjYo8iJ8/f17jx49XzZo15ePjo1tuuUWTJk2SMcaqMcZowoQJqlKlinx8fBQZGam9e/c6befEiRPq16+f/Pz8FBAQoIEDByozM7Oo2wUAAAAAwFZFHsSnTJmi2bNn64033tDu3bs1ZcoUTZ06Va+//rpVM3XqVM2cOVNz5sxRYmKifH19FRUVpbNnz1o1/fr1065duxQfH68VK1Zow4YNGjx4cFG3CwAAAACArTyKeoObNm1Sjx49FB0dLUmqUaOGFi1apC1btkj6/Wz4jBkz9Oyzz6pHjx6SpA8++EAhISFasmSJ+vbtq927dysuLk5bt25V8+bNJUmvv/66unXrpmnTpiksLOyi/WZnZys7O9uadjgcRX1oAAAAAABcsyI/I966dWutXr1ae/bskSR9++23+vrrr9W1a1dJ0oEDB5SamqrIyEhrHX9/f7Vs2VIJCQmSpISEBAUEBFghXJIiIyPl7u6uxMTEfPcbGxsrf39/6xUeHl7UhwYAAAAAwDUr8jPiY8eOlcPhUN26dVWmTBmdP39eL730kvr16ydJSk1NlSSFhIQ4rRcSEmItS01NVXBwsHOjHh4KCgqyav5s3LhxGjlypDXtcDgI4wAAAACA606RB/H//Oc/WrBggRYuXKgGDRooOTlZI0aMUFhYmGJiYop6dxYvLy95eXm5bPsAAAAAABSFIg/io0aN0tixY9W3b19JUsOGDfXTTz8pNjZWMTExCg0NlSSlpaWpSpUq1nppaWlq0qSJJCk0NFTHjh1z2m5ubq5OnDhhrQ8AAAAAQElU5N8RP336tNzdnTdbpkwZ5eXlSZJq1qyp0NBQrV692lrucDiUmJioiIgISVJERITS09OVlJRk1axZs0Z5eXlq2bJlUbcMAAAAAIBtivyMePfu3fXSSy+pWrVqatCggbZv367p06frkUcekSS5ublpxIgRevHFF3XrrbeqZs2aGj9+vMLCwtSzZ09JUr169dSlSxcNGjRIc+bMUU5OjoYNG6a+ffvme8d0AAAAAABKiiIP4q+//rrGjx+vv//97zp27JjCwsL02GOPacKECVbN6NGjlZWVpcGDBys9PV133nmn4uLi5O3tbdUsWLBAw4YNU6dOneTu7q5evXpp5syZRd0uAAAAAAC2cjPGmOJuwhUcDof8/f2VkZEhPz+/4m6nUGqM/ay4Wyh1Dk6OLu4WSh3Guf0Y5wAAAK5V0Bxa5N8RBwAAAAAAl0YQBwAAAADARgRxAAAAAABsRBAHAAAAAMBGBHEAAAAAAGxEEAcAAAAAwEYEcQAAAAAAbEQQBwAAAADARgRxAAAAAABsRBAHAAAAAMBGBHEAAAAAAGxEEAcAAAAAwEYEcQAAAAAAbEQQBwAAAADARgRxAAAAAABsRBAHAAAAAMBGBHEAAAAAAGxEEAcAAAAAwEYEcQAAAAAAbEQQBwAAAADARgRxAAAAAABsRBAHAAAAAMBGBHEAAAAAAGxEEAcAAAAAwEYEcQAAAAAAbEQQBwAAAADARgRxAAAAAABsRBAHAAAAAMBGBHEAAAAAAGxEEAcAAAAAwEYEcQAAAAAAbEQQBwAAAADARgRxAAAAAABsRBAHAAAAAMBGBHEAAAAAAGxEEAcAAAAAwEYEcQAAAAAAbEQQBwAAAADARgRxAAAAAABsRBAHAAAAAMBGBHEAAAAAAGxEEAcAAAAAwEYEcQAAAAAAbEQQBwAAAADARgRxAAAAAABs5JIg/ssvv+hvf/ubKlasKB8fHzVs2FDbtm2zlhtjNGHCBFWpUkU+Pj6KjIzU3r17nbZx4sQJ9evXT35+fgoICNDAgQOVmZnpinYBAAAAALBNkQfxkydPqk2bNipbtqxWrlyp77//Xv/85z8VGBho1UydOlUzZ87UnDlzlJiYKF9fX0VFRens2bNWTb9+/bRr1y7Fx8drxYoV2rBhgwYPHlzU7QIAAAAAYCuPot7glClTFB4errlz51rzatasaf3bGKMZM2bo2WefVY8ePSRJH3zwgUJCQrRkyRL17dtXu3fvVlxcnLZu3armzZtLkl5//XV169ZN06ZNU1hY2EX7zc7OVnZ2tjXtcDiK+tAAAAAAALhmRX5GfNmyZWrevLl69+6t4OBgNW3aVO+88461/MCBA0pNTVVkZKQ1z9/fXy1btlRCQoIkKSEhQQEBAVYIl6TIyEi5u7srMTEx3/3GxsbK39/feoWHhxf1oQEAAAAAcM2KPIj/+OOPmj17tm699VZ98cUXGjJkiJ544gnNnz9fkpSamipJCgkJcVovJCTEWpaamqrg4GCn5R4eHgoKCrJq/mzcuHHKyMiwXocPHy7qQwMAAAAA4JoV+aXpeXl5at68uV5++WVJUtOmTfXdd99pzpw5iomJKerdWby8vOTl5eWy7QMAAAAAUBSK/Ix4lSpVVL9+fad59erV06FDhyRJoaGhkqS0tDSnmrS0NGtZaGiojh075rQ8NzdXJ06csGoAAAAAACiJijyIt2nTRikpKU7z9uzZo+rVq0v6/cZtoaGhWr16tbXc4XAoMTFRERERkqSIiAilp6crKSnJqlmzZo3y8vLUsmXLom4ZAAAAAADbFPml6U899ZRat26tl19+WX369NGWLVv09ttv6+2335Ykubm5acSIEXrxxRd16623qmbNmho/frzCwsLUs2dPSb+fQe/SpYsGDRqkOXPmKCcnR8OGDVPfvn3zvWM6AAAAAAAlRZEH8RYtWmjx4sUaN26cXnjhBdWsWVMzZsxQv379rJrRo0crKytLgwcPVnp6uu68807FxcXJ29vbqlmwYIGGDRumTp06yd3dXb169dLMmTOLul0AAAAAAGzlZowxxd2EKzgcDvn7+ysjI0N+fn7F3U6h1Bj7WXG3UOocnBxd3C2UOoxz+zHOAQAAXKugObTIvyMOAAAAAAAujSAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAEApMHv2bDVq1Eh+fn7y8/NTRESEVq5caS1PTU1V//79FRoaKl9fX91+++365JNPnLZxzz33qFq1avL29laVKlXUv39/HTlyxO5DAQCgxHN5EJ88ebLc3Nw0YsQIa97Zs2c1dOhQVaxYUeXLl1evXr2UlpbmtN6hQ4cUHR2tcuXKKTg4WKNGjVJubq6r2wUA4IZUtWpVTZ48WUlJSdq2bZvuuusu9ejRQ7t27ZIkPfTQQ0pJSdGyZcu0c+dO3XvvverTp4+2b99ubaNjx476z3/+o5SUFH3yySfav3+/7rvvvuI6JAAASiyXBvGtW7fqrbfeUqNGjZzmP/XUU1q+fLk+/vhjrV+/XkeOHNG9995rLT9//ryio6N17tw5bdq0SfPnz9e8efM0YcIEV7YLAMANq3v37urWrZtuvfVW1a5dWy+99JLKly+vzZs3S5I2bdqk4cOH64477tDNN9+sZ599VgEBAUpKSrK28dRTT6lVq1aqXr26WrdurbFjx2rz5s3KyckprsMCAKBEclkQz8zMVL9+/fTOO+8oMDDQmp+RkaH33ntP06dP11133aVmzZpp7ty52rRpk/XHwKpVq/T999/r3//+t5o0aaKuXbtq0qRJmjVrls6dO+eqlgEAKBXOnz+vDz/8UFlZWYqIiJAktW7dWh999JFOnDihvLw8ffjhhzp79qw6dOiQ7zZOnDihBQsWqHXr1ipbtqyN3QMAUPK5LIgPHTpU0dHRioyMdJqflJSknJwcp/l169ZVtWrVlJCQIElKSEhQw4YNFRISYtVERUXJ4XBYl9D9WXZ2thwOh9MLAAD8z86dO1W+fHl5eXnp8ccf1+LFi1W/fn1J0n/+8x/l5OSoYsWK8vLy0mOPPabFixerVq1aTtsYM2aMfH19VbFiRR06dEhLly4tjkMBAKBEc0kQ//DDD/XNN98oNjb2omWpqany9PRUQECA0/yQkBClpqZaNX8M4ReWX1iWn9jYWPn7+1uv8PDwIjgSAABuHHXq1FFycrISExM1ZMgQxcTE6Pvvv5ckjR8/Xunp6fryyy+1bds2jRw5Un369NHOnTudtjFq1Cht375dq1atUpkyZfTQQw/JGFMchwMAQInlUdQbPHz4sJ588knFx8fL29u7qDd/SePGjdPIkSOtaYfDQRgHAOAPPD09rTPczZo109atW/Xaa69p9OjReuONN/Tdd9+pQYMGkqTGjRvrq6++0qxZszRnzhxrG5UqVVKlSpVUu3Zt1atXT+Hh4dq8ebN1iTsAALiyIj8jnpSUpGPHjun222+Xh4eHPDw8tH79es2cOVMeHh4KCQnRuXPnlJ6e7rReWlqaQkNDJUmhoaEX3UX9wvSFmj/z8vKyHsly4QUAAC4tLy9P2dnZOn36tCTJ3d35z4IyZcooLy/vsutLv389DAAAFFyRnxHv1KnTRZexPfzww6pbt67GjBmj8PBwlS1bVqtXr1avXr0kSSkpKTp06JD1aXpERIReeuklHTt2TMHBwZKk+Ph4+fn5Wd9lAwAABTdu3Dh17dpV1apV06lTp7Rw4UKtW7dOX3zxherWratatWrpscce07Rp01SxYkUtWbJE8fHxWrFihSQpMTFRW7du1Z133qnAwEDt379f48eP1y233MLZcAAACsnN2PDFrg4dOqhJkyaaMWOGJGnIkCH6/PPPNW/ePPn5+Wn48OGSfn90ivT73VybNGmisLAwTZ06Vampqerfv78effRRvfzyywXap8PhkL+/vzIyMkrc2fEaYz8r7hZKnYOTo4u7hVKHcW4/xrn9rqdxfvzz13T2p291PuuE3L185Vm5hvxa3iefmk0lSTknflH6+vk6+/P3Mjln5BFQRX533Kvyt90lSTr360Gd+PJt5Rw7oLycsypTPkg+NW+Xf+v75VGhUnEemhPGOQCgOBU0hxb5GfGCePXVV+Xu7q5evXopOztbUVFRevPNN63lZcqU0YoVKzRkyBBFRETI19dXMTExeuGFF4qjXQAASrxK3Z687PKyQTep8l//75LLPSvXUOgDBfswHAAAXJ4tQXzdunVO097e3po1a5ZmzZp1yXWqV6+uzz//3MWdAQAAAABgL5c9RxwAAAAAAFyMIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2KjIg3hsbKxatGihChUqKDg4WD179lRKSopTzdmzZzV06FBVrFhR5cuXV69evZSWluZUc+jQIUVHR6tcuXIKDg7WqFGjlJubW9TtAgAAAABgqyIP4uvXr9fQoUO1efNmxcfHKycnR507d1ZWVpZV89RTT2n58uX6+OOPtX79eh05ckT33nuvtfz8+fOKjo7WuXPntGnTJs2fP1/z5s3ThAkTirpdAAAAAABs5VHUG4yLi3OanjdvnoKDg5WUlKR27dopIyND7733nhYuXKi77rpLkjR37lzVq1dPmzdvVqtWrbRq1Sp9//33+vLLLxUSEqImTZpo0qRJGjNmjCZOnChPT8+L9pudna3s7Gxr2uFwFPWhAQAAAABwzVz+HfGMjAxJUlBQkCQpKSlJOTk5ioyMtGrq1q2ratWqKSEhQZKUkJCghg0bKiQkxKqJioqSw+HQrl278t1PbGys/P39rVd4eLirDgkAAAAAgKvm0iCel5enESNGqE2bNrrtttskSampqfL09FRAQIBTbUhIiFJTU62aP4bwC8svLMvPuHHjlJGRYb0OHz5cxEcDAAAAAMC1K/JL0/9o6NCh+u677/T111+7cjeSJC8vL3l5ebl8PwAAAAAAXAuXnREfNmyYVqxYobVr16pq1arW/NDQUJ07d07p6elO9WlpaQoNDbVq/nwX9QvTF2oAAAAAACiJijyIG2M0bNgwLV68WGvWrFHNmjWdljdr1kxly5bV6tWrrXkpKSk6dOiQIiIiJEkRERHauXOnjh07ZtXEx8fLz89P9evXL+qWAQAAAACwTZFfmj506FAtXLhQS5cuVYUKFazvdPv7+8vHx0f+/v4aOHCgRo4cqaCgIPn5+Wn48OGKiIhQq1atJEmdO3dW/fr11b9/f02dOlWpqal69tlnNXToUC4/BwAAAACUaEUexGfPni1J6tChg9P8uXPnasCAAZKkV199Ve7u7urVq5eys7MVFRWlN99806otU6aMVqxYoSFDhigiIkK+vr6KiYnRCy+8UNTtAgAAAABgqyIP4saYK9Z4e3tr1qxZmjVr1iVrqlevrs8//7woWwMAAAAAoNi5/DniAAAAAADgfwjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAAAAAICNCOIAAAAAANiIIA4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAACAG1JsbKxatGihChUqKDg4WD179lRKSkq+tcYYde3aVW5ublqyZIm9jQIodQjiAAAAuCGtX79eQ4cO1ebNmxUfH6+cnBx17txZWVlZF9XOmDFDbm5uxdAlgNLIo7gbAAAAAFwhLi7OaXrevHkKDg5WUlKS2rVrZ81PTk7WP//5T23btk1VqlSxu00ApRBnxAEAAFAqZGRkSJKCgoKseadPn9aDDz6oWbNmKTQ0tLhaA67Jhg0b1L17d4WFheX79YqJEyeqbt268vX1VWBgoCIjI5WYmFg8zUISQRwAAAClQF5enkaMGKE2bdrotttus+Y/9dRTat26tXr06FGM3QHXJisrS40bN9asWbPyXV67dm298cYb2rlzp77++mvVqFFDnTt31q+//mpzp7iAS9MBAABwwxs6dKi+++47ff3119a8ZcuWac2aNdq+fXsxdgZcu65du6pr166XXP7ggw86TU+fPl3vvfeeduzYoU6dOrm6PeSDM+IAAAC4oQ0bNkwrVqzQ2rVrVbVqVWv+mjVrtH//fgUEBMjDw0MeHr+fo+rVq5c6dOhQTN0CrnXu3Dm9/fbb8vf3V+PGjYu7nVKLM+IAAAC4IRljNHz4cC1evFjr1q1TzZo1nZaPHTtWjz76qNO8hg0b6tVXX1X37t3tbBVwuRUrVqhv3746ffq0qlSpovj4eFWqVKm42yq1COIAAAC4IQ0dOlQLFy7U0qVLVaFCBaWmpkqS/P395ePjo9DQ0Hxv0FatWrWLQjtQ0nXs2FHJyck6fvy43nnnHfXp00eJiYkKDg4u7tZKJYI4AAAArlqNsZ8VdwuX9NPs2ZJ00WXmFbuNUPmGkZdcb/AH2zRic1lXtnZNDk6OLu4WUAL5+vqqVq1aqlWrllq1aqVbb71V7733nsaNG1fcrZVKBHEAAADckKqPWWHLOkBJlJeXp+zs7OJuo9QiiAMAAABACZaZmal9+/ZZ0wcOHFBycrKCgoJUsWJFvfTSS7rnnntUpUoVHT9+XLNmzdIvv/yi3r17F2PXpRtBHAAAAAAu43r+CoYknT20Q2mL/s+aHjlypCTJ97ZOqhg1VL8uX6epr7+l82ccKuPjJ8/QWxV4f6yi/3VQ0sHiaPmKbvSvYFzXQXzWrFl65ZVXlJqaqsaNG+v111/XHXfcUdxtAQAAAMB1w7tao8t+rSL4r/+wsRsUxHX7HPGPPvpII0eO1HPPPadvvvlGjRs3VlRUlI4dO1bcrQEAAAAAcNWu2zPi06dP16BBg/Twww9LkubMmaPPPvtM77//vsaOHXtRfXZ2ttPNBjIyMiRJDofDnoaLUF726eJuodQpieOkpGOc249xbj/Guf0Y5/ZjnNuPcW4/xrn9Suo4v9C3MeaydW7mShXF4Ny5cypXrpz++9//qmfPntb8mJgYpaena+nSpRetM3HiRD3//PM2dgkAAAAAwMUOHz6sqlWrXnL5dXlG/Pjx4zp//rxCQkKc5oeEhOiHH37Id51x48ZZNyWQfr8d/4kTJ1SxYkW5ubm5tF/8zuFwKDw8XIcPH5afn19xtwO4BOMcpQHjHKUB4xylAePcfsYYnTp1SmFhYZetuy6D+NXw8vKSl5eX07yAgIDiaaaU8/Pz4xcdNzzGOUoDxjlKA8Y5SgPGub38/f2vWHNd3qytUqVKKlOmjNLS0pzmp6WlKTQ0tJi6AgAAAADg2l2XQdzT01PNmjXT6tWrrXl5eXlavXq1IiIiirEzAAAAAACuzXV7afrIkSMVExOj5s2b64477tCMGTOUlZVl3UUd1x8vLy8999xzF31FALiRMM5RGjDOURowzlEaMM6vX9flXdMveOONN/TKK68oNTVVTZo00cyZM9WyZcvibgsAAAAAgKt2XQdxAAAAAABuNNfld8QBAAAAALhREcQBAAAAALARQRwAAAAAABsRxAEAAAAAsNF1+/gyXL9ycnJUmHv8ubu7y8ODoYaS5cknn9Svv/5a4PpbbrlFkyZNcmFHAAAAuFFw13QUWu3atVW1atUrhnE3NzcZY5SVlaUtW7bY1B1QNBo3bqxly5YVqNYYoz59+jDOUeIsWrRIp06dKnB9cHCwevbs6bqGABfo1auXjh49WuD6+vXr691333VhR0DRY5yXPJymRKH5+vpqzZo1Ba5v0aKFC7sBXMPd3V3Vq1cvcD2faaIkeumllzR69OgCj9+XX36ZII4S58cff9T27dsLXH/HHXe4sBvANRjnJQ9BHIXm5ubm0nrgesA4R2lQtmxZPfTQQwWuf+ONN1zYDeAa/P+M0oBxXvJwszYAAEopPnACAKB4EMQBAAAAALARl6YDQD7OnDmjF154oUC1fD8cAAAAhUEQR6F5enqqdevWBa6vVKmSC7sBXOOtt97SmTNnClwfFRXlwm4A18jJydGGDRsKVGuM4UMnlEhZWVl65JFHClTLOEdJxTgveQjiKLQ77rijUM9XrlWrlgu7AVyjXbt2xd0C4HL9+/fXypUrC1w/YMAA1zUDuMjKlSuVk5NT4HofHx8XdgO4BuO85OE54ii0Jk2aaNmyZQX+JK137948XxkArkM5OTmFOivi7u4uDw8+w0fJsmjRIp06darA9cHBwTymDyUO47zkIYij0Jo2bVqo5xS2aNFCW7dudWFHAICrUbt2bVWtWrVAtcYYnT59WomJiS7uCihat912m0aPHl3gD51mzZrFCQSUOIzzkoePtVFoPO4GAG4Mvr6+WrNmTYHrW7Ro4cJuANcoW7asHnrooQLXv/HGGy7sBnANxnnJw+PLAAAopfhgFaUB4xylAeO85CGIAwAAAABgIy5NR6HxfGUAAAAAuHoEcRQaz1cGAAAlRU5OjjZs2FCgWp6vjJKKcV7yEMRRaDxfGQBuDJ6enmrdunWB6ytVquTCbgDX6N+/v1auXFng+gEDBriuGcBFGOclD48vAwCglHriiSf066+/Fri+Vq1amjRpkgs7AopeTk5Ooc7+ubu7y8ODc1UoWRjnJQ9BHACAUqpJkyZatmxZgf946927N8+dRYlTu3ZtVa1atUC1xhidPn1aiYmJLu4KKFqM85KHj0EAACil3NzcVK1atQLX89k9SiJfX1+tWbOmwPUtWrRwYTeAazDOSx4eXwYAQCnFc2dRGjDOURowzksegjgAAAAAADYiiAMAAAAAYCO+Iw4AQCl15swZvfDCCwWq5fvhAAAUHYI4AACl1FtvvaUzZ84UuD4qKsqF3QCu4enpqdatWxe4vlKlSi7sBnANxnnJQxAHAKCUateuXXG3ALjcHXfcoV9//bXA9bVq1XJhN4BrMM5LHp4jDgAAgBtWkyZNtGzZsgJ/vaJ3797asmWLi7sCihbjvOThjDgAAABuWG5ubqpWrVqB6zlHhZKIcV7ycNd0AAAA3LB4vjJKA8Z5yUMQBwAAAADARgRxAAAAAABsxHfEAQAAcMM6c+aMXnjhhQLV8r1ZlFSM85KHu6YDAADghrVhwwadOXOmwPX+/v5q1aqVCzsCih7jvOQhiAMAAAAAYCO+Iw4AAAAAgI0I4gAAAAAA2IggDgAAAACAjQjiAAAAAADYiCAOAC7SoUMHjRgxorjbuKQaNWpoxowZJWa7RcnNzU1Lliwp7jZcYuLEiWrSpEmRbvPgwYNyc3NTcnJykW63JJk3b54CAgJcug9XvHf5uZHHPwCUFARxAHCRTz/9VJMmTSpQbUkPOvPnz9edd94pSdq6dasGDx5c4HXXrVsnNzc3paenu6g713jnnXfUtm1bBQYGKjAwUJGRkdqyZUuB1x8wYIDc3NycXl26dLnsOvPmzbtonQuvY8eOXeshuVxBP5w6e/asBgwYoIYNG8rDw0M9e/Z0eW+lydGjR9W1a9cC1xfmQ4i3335bHTp0kJ+f32V/rz/77DO1bNlSPj4+CgwMvOg93rp1qzp16qSAgAAFBgYqKipK3377rVONMUbTpk1T7dq15eXlpZtuukkvvfRSgY8LAIoTQRwAXCQoKEgVKlSwfb85OTm273Pp0qW65557JEmVK1dWuXLlbO/BGKPc3Fzb9rdu3To98MADWrt2rRISEhQeHq7OnTvrl19+KfA2unTpoqNHj1qvRYsWXbb+/vvvd6o/evSooqKi1L59ewUHB1/rIV03zp8/Lx8fHz3xxBOKjIws7nZuOKGhofLy8nLJtk+fPq0uXbro//7v/y5Z88knn6h///56+OGH9e2332rjxo168MEHreWZmZnq0qWLqlWrpsTERH399deqUKGCoqKinP5/e/LJJ/Xuu+9q2rRp+uGHH7Rs2TLdcccdLjkuAChyBgDgEu3btzdPPvmkMcaY6tWrm5deesk8/PDDpnz58iY8PNy89dZbVq0kp1f79u2tZe+8846pW7eu8fLyMnXq1DGzZs2ylh04cMBIMh9++KFp166d8fLyMnPnzjUxMTGmR48e5pVXXjGhoaEmKCjI/P3vfzfnzp2z1q1evbp59dVXnXqYM2eOiY6ONj4+PqZu3bpm06ZNZu/evaZ9+/amXLlyJiIiwuzbt8/pOM+cOWN8fX3N7t27L7ndd955x/Ts2dP4+PiYWrVqmaVLlzr1/8dXTEyMMcaY8+fPm5dfftnUqFHDeHt7m0aNGpmPP/7Y2u7atWuNJPP555+b22+/3ZQtW9asXbvWtG/f3gwfPtyMGjXKBAYGmpCQEPPcc8859SzJLF682KmHjz76yNx5553G29vbNG/e3KSkpJgtW7aYZs2aGV9fX9OlSxdz7NixS77fubm5pkKFCmb+/PmXrPmjC+/RtTh27JgpW7as+eCDD6x5zz33nGncuLGZM2eOqVq1qvHx8TG9e/c26enpl93W+fPnzZQpU8wtt9xiPD09TXh4uHnxxReNMf/7GX3yySemQ4cOxsfHxzRq1Mhs2rTJWv/48eOmb9++JiwszPj4+JjbbrvNLFy40Ol4//xeHzhw4IrHeKmf04XjfO+990x4eLjx9fU1Q4YMMbm5uWbKlCkmJCTEVK5c2TqGgjh58qQZPHiwCQ4ONl5eXqZBgwZm+fLlxhhj5s6da/z9/U1cXJypW7eu8fX1NVFRUebIkSNO27jc76sxxhw+fNj07dvXBAYGmnLlyplmzZqZzZs3Ox3TBfv27TM1a9Y0Q4cONXl5eVYPixcvNrVq1TJeXl6mc+fO5tChQ077ePPNN83NN99sypYta2rXru00PozJf/xf6r298Hv2x9eff5/yc2G9kydPOs3PyckxN910k3n33Xcvue7WrVuNJKfj2rFjh5Fk9u7da4wx5vvvvzceHh7mhx9+uGIvAHA9IogDgIv8OYgHBQWZWbNmmb1795rY2Fjj7u5u/RG5ZcsWI8l8+eWX5ujRo+a3334zxhjz73//21SpUsV88skn5scffzSffPKJCQoKMvPmzTPG/O+P6Bo1alg1R44cMTExMcbPz888/vjjZvfu3Wb58uWmXLly5u2337b6yy8w33TTTeajjz4yKSkppmfPnqZGjRrmrrvuMnFxceb77783rVq1Ml26dHE6zhUrVpjatWtfdrtVq1Y1CxcuNHv37jVPPPGEKV++vPntt99Mbm6u+eSTT4wkk5KSYo4ePWoFxhdffNHUrVvXxMXFmf3795u5c+caLy8vs27dOmPM//7Qb9SokVm1apXZt2+f+e2330z79u2Nn5+fmThxotmzZ4+ZP3++cXNzM6tWrXLq6c9B5MK+Lhxns2bNTIcOHczXX39tvvnmG1OrVi3z+OOPX/L9djgcxtvb2wpuVxITE2P8/f1N5cqVTe3atc3jjz9ujh8/XqB1L5g2bZrx9/c3p0+ftuY999xzxtfX19x1111m+/btZv369aZWrVrmwQcfvOy2Ro8ebQIDA828efPMvn37zFdffWXeeecdY4zzz2jFihUmJSXF3HfffaZ69eomJyfHGGPMzz//bF555RWzfft2s3//fjNz5kxTpkwZk5iYaIwxJj093URERJhBgwaZo0ePmqNHj5rc3NwC/ZwuFcTLly9v7rvvPrNr1y6zbNky4+npaaKioszw4cPNDz/8YN5//30jyQq6l3P+/HnTqlUr06BBA7Nq1Sqzf/9+s3z5cvP5558bY34P4mXLljWRkZFm69atJikpydSrV8/p53ql39dTp06Zm2++2bRt29Z89dVXZu/eveajjz6yQu8fg/i3335rQkNDzT/+8Q9r+xd6aN68udm0aZPZtm2bueOOO0zr1q2tmk8//dSULVvWzJo1y6SkpJh//vOfpkyZMmbNmjVWzaXGf37vbXZ2tpkxY4bx8/Oz3rdTp05d8ed5qSCemJhoJJn333/fNGnSxISGhpouXbqYnTt3WjUOh8NUrFjRPPfccyY7O9ucPn3aPPnkk6ZevXrWeJsyZYqpXbu2mTZtmqlRo4apXr26GThwoPV/JwBc7wjiAOAifw7if/vb36xleXl5Jjg42MyePdsY878/hrdv3+60jVtuucXprKIxxkyaNMlEREQ4rTdjxgynmpiYGFO9enWnoNO7d29z//33W9P5BeZnn33Wmk5ISDCSzHvvvWfNW7RokfH29nba16BBg8wzzzxT4O1mZmYaSWblypXGmPz/YD979qwpV66c0xlXY4wZOHCgeeCBB5zWW7JkiVNN+/btzZ133uk0r0WLFmbMmDFOPf05iPzxDN2iRYuMJLN69WprXmxsrKlTp465lCFDhpibb77ZnDlz5pI1f7Ro0SKzdOlSs2PHDrN48WJTr14906JFiwKF0wvq1atnhgwZ4jTvueeeM2XKlDE///yzNW/lypXG3d3dHD16NN/tOBwO4+XlZQXvP8vvZ7Rr1y4jyboSIj/R0dHm6aeftqb/+DtRUJcL4uXKlTMOh8OaFxUVZWrUqGHOnz9vzatTp46JjY294n6++OIL4+7ublJSUvJdPnfuXCPJ6YqQWbNmmZCQEGv6Sr+vb731lqlQocIlw+KFIL5x40YTGBhopk2blm8Pf/xgYffu3UaS9YFH69atzaBBg5zW6927t+nWrZs1faXx/+f39sKZ+MK4VBC/8LtVrVo189///tds27bNPPDAA6ZixYpOP5edO3eaW265xbi7uxt3d3dTp04dc/DgQWv5Y489Zry8vEzLli3Nhg0bzNq1a02TJk1Mx44dC9UnABQXviMOADZp1KiR9W83NzeFhoZe9gZbWVlZ2r9/vwYOHKjy5ctbrxdffFH79+93qm3evPlF6zdo0EBlypSxpqtUqXLFG3r9sceQkBBJUsOGDZ3mnT17Vg6HQ9Lv38tevny59f3wgmzX19dXfn5+l+1l3759On36tO6++26nY//ggw8KdOx/3J9UdMd+qW1MnjxZH374oRYvXixvb+/L7ueCvn376p577lHDhg3Vs2dPrVixQlu3btW6deskSV27drWOu0GDBhetn5CQoN27d2vgwIEXLatWrZpuuukmazoiIkJ5eXlKSUnRV1995fQzXbBggXbv3q3s7Gx16tTpsj3/8WdUpUoVSbJ+JufPn9ekSZPUsGFDBQUFqXz58vriiy906NChy26zQYMGVi+FuYGY9Psd+v94H4aQkBDVr19f7u7uTvMKciO75ORkVa1aVbVr175kTbly5XTLLbdY038cVwX5fU1OTlbTpk0VFBR0yX0cOnRId999tyZMmKCnn376ouUeHh5q0aKFNV23bl0FBARo9+7dkqTdu3erTZs2Tuu0adPGWn4pl3tv8/Pyyy87HeeV3ucL8vLyJEn/+Mc/1KtXLzVr1kxz586Vm5ubPv74Y0nSmTNnNHDgQLVp00abN2/Wxo0bddtttyk6OlpnzpyxtpOdna0PPvhAbdu2VYcOHfTee+9p7dq1SklJKVAvAFCcPIq7AQAoLcqWLes07ebmZv1Rmp/MzExJv9+du2XLlk7L/hiwpd/D7bXu78/ruLm5XXLehe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size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 19981 (\\N{CJK UNIFIED IDEOGRAPH-4E0D}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 26159 (\\N{CJK UNIFIED IDEOGRAPH-662F}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from font(s) 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'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"data":{"image/png":"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size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 19981 (\\N{CJK UNIFIED IDEOGRAPH-4E0D}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 26159 (\\N{CJK UNIFIED IDEOGRAPH-662F}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from font(s) 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'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 19981 (\\N{CJK UNIFIED IDEOGRAPH-4E0D}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 26159 (\\N{CJK UNIFIED IDEOGRAPH-662F}) missing from font(s) DejaVu Sans.\n","  fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llama-factory/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from font(s) 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found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-3372 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-3372\n","不是      1338\n","是       1006\n","不重要      598\n","回答正确      30\n","问法错误      28\n","Name: count, dtype: int64\n"]},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA+IAAAIkCAYAAACa3JFWAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAABM8ElEQVR4nO3de5xN9f7H8fceYy6GuWFmTMal5JpLuQ6KajIicYiUoykOp85QUsg5UahGcgon0cVBv0Op0yFUcsslxqWJE9KECDEz1TQzDMZcvr8/eljHztCo2d+ZMa/n47Eej/Zan7XW5zt77R7ee+21lssYYwQAAAAAAKzwKukGAAAAAAAoTwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWHTZQXzDhg3q0aOHIiMj5XK5tGTJkovWPvjgg3K5XJo2bZrb/PT0dA0YMECBgYEKDg7W4MGDdfLkSbeaL774QjfeeKP8/PwUFRWlKVOmXG6rAAAAAACUOt6Xu0J2draaN2+uQYMGqXfv3hetW7x4sbZs2aLIyMgLlg0YMEDHjx/XqlWrlJubqwceeEBDhw7VwoULJUlZWVnq0qWLYmJiNHv2bO3atUuDBg1ScHCwhg4dWqQ+CwoKdOzYMVWpUkUul+tyhwkAAAAAwGUxxujEiROKjIyUl9clznub30GSWbx48QXzjx49aq666iqze/duU7t2bfPSSy85y7788ksjyWzfvt2Z99FHHxmXy2W+++47Y4wxr7zyigkJCTE5OTlOzZgxY0yDBg2K3NuRI0eMJCYmJiYmJiYmJiYmJiYmq9ORI0cumVcv+4z4rykoKNDAgQM1atQoNWnS5ILliYmJCg4OVqtWrZx5MTEx8vLy0tatW/WHP/xBiYmJuummm+Tj4+PUxMbG6vnnn9dPP/2kkJCQC7abk5OjnJwc5/XP3xNIR44cUWBgYHEOEQAAAACAC2RlZSkqKkpVqlS5ZF2xB/Hnn39e3t7eevjhhwtdnpKSorCwMPcmvL0VGhqqlJQUp6Zu3bpuNeHh4c6ywoJ4QkKCJkyYcMH8wMBAgjgAAAAAwJpfuzy6WO+anpSUpOnTp2vevHnWr8seO3asMjMznenIkSNW9w8AAAAAQFEUaxDfuHGj0tLSVKtWLXl7e8vb21vffvutHnvsMdWpU0eSFBERobS0NLf18vLylJ6eroiICKcmNTXVrebc63M1v+Tr6+uc/eYsOAAAAACgtCrWID5w4EB98cUX2rlzpzNFRkZq1KhR+vjjjyVJ0dHRysjIUFJSkrPe2rVrVVBQoLZt2zo1GzZsUG5urlOzatUqNWjQoNCfpQMAAAAAUFZc9jXiJ0+e1P79+53XBw8e1M6dOxUaGqpatWqpatWqbvUVK1ZURESEGjRoIElq1KiRunbtqiFDhmj27NnKzc3VsGHD1L9/f+dRZ/fee68mTJigwYMHa8yYMdq9e7emT5+ul1566feMFQAAAACAEnfZQfyzzz7TzTff7LweOXKkJCkuLk7z5s0r0jYWLFigYcOG6dZbb5WXl5f69OmjGTNmOMuDgoK0cuVKxcfHq2XLlqpWrZrGjx9f5GeIAwAAAABQWrnMued8XWGysrIUFBSkzMxMrhcHAAAAAHhcUXNosV4jDgAAAAAALo0gDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRxuNmzYoB49eigyMlIul0tLlixxW/7000+rYcOGCggIUEhIiGJiYrR161a3mjvvvFO1atWSn5+fatSooYEDB+rYsWNuNR9//LHatWunKlWqqHr16urTp48OHTrk4dEBAAAAQMkjiMNNdna2mjdvrpkzZxa6vH79+nr55Ze1a9cuffrpp6pTp466dOmi77//3qm5+eab9c477yg5OVnvvfeeDhw4oLvuustZfvDgQfXs2VO33HKLdu7cqY8//lg//PCDevfu7fHxAQAAAEBJ4/FluCiXy6XFixerV69eF60593devXq1br311kJrli5dql69eiknJ0cVK1bUv//9b91zzz3KycmRl9fP3wUtW7ZMPXv2dGoAAAAAoKzh8WXwuLNnz+q1115TUFCQmjdvXmhNenq6FixYoPbt2zsBu2XLlvLy8tLcuXOVn5+vzMxM/d///Z9iYmII4QAAAACueARxXLbly5ercuXK8vPz00svvaRVq1apWrVqbjVjxoxRQECAqlatqsOHD+v99993ltWtW1crV67UX//6V/n6+io4OFhHjx7VO++8Y3soAAAAAGAdQRyX7eabb9bOnTu1efNmde3aVf369VNaWppbzahRo7Rjxw6tXLlSFSpU0H333adzV0GkpKRoyJAhiouL0/bt27V+/Xr5+Pjorrvu0hV6pQQAAAAAOLhGHBdVlGvEJenaa6/VoEGDNHbs2EKXHz16VFFRUdq8ebOio6M1btw4rVixQtu3b7+gJjExUe3atSvOYQAAAACAFVwjDmsKCgqUk5NzyeWSnJpTp045N2k7p0KFCm61AAAAAHCl8i7pBlC6nDx5Uvv373deHzx4UDt37lRoaKiqVq2qZ599Vnfeeadq1KihH374QTNnztR3332nvn37SpK2bt2q7du3q2PHjgoJCdGBAwc0btw4XXPNNYqOjpYkde/eXS+99JImTpyoe+65RydOnNBf//pX1a5dW9dff32JjBsAAAAAbOGn6aVQnSc+KLF9nzn8hVLf+usF8wOuu1VVY+P1/bIXdPZYsvJPZ6mCf6B8Iq5VUPu75VujviTp7PeHlL76NeWmHVRB7hlVqBwq/7o3KKj93fKu8r8bumV/uV5Z2/6j3PTv5KroK9/IhgrpfL8qVo2yNtbzHZrcvUT2CwAAAODKUdQcShAvhUoyiJdXBHEAAAAAvxfXiAMAAAAAUAoRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwKLLDuIbNmxQjx49FBkZKZfLpSVLljjLcnNzNWbMGDVt2lQBAQGKjIzUfffdp2PHjrltIz09XQMGDFBgYKCCg4M1ePBgnTx50q3miy++0I033ig/Pz9FRUVpypQpv22EAAAAAACUIpcdxLOzs9W8eXPNnDnzgmWnTp3S559/rnHjxunzzz/Xf/7zHyUnJ+vOO+90qxswYID27NmjVatWafny5dqwYYOGDh3qLM/KylKXLl1Uu3ZtJSUl6YUXXtDTTz+t11577TcMEQAAAACA0sNljDG/eWWXS4sXL1avXr0uWrN9+3a1adNG3377rWrVqqW9e/eqcePG2r59u1q1aiVJWrFihbp166ajR48qMjJSs2bN0t/+9jelpKTIx8dHkvTEE09oyZIl+uqrrwrdT05OjnJycpzXWVlZioqKUmZmpgIDA3/rEEtEnSc+KOkWyp1Dk7uXdAsAAAAAyrisrCwFBQX9ag71+DXimZmZcrlcCg4OliQlJiYqODjYCeGSFBMTIy8vL23dutWpuemmm5wQLkmxsbFKTk7WTz/9VOh+EhISFBQU5ExRUVGeGxQAAAAAAL+RR4P4mTNnNGbMGN1zzz3OtwEpKSkKCwtzq/P29lZoaKhSUlKcmvDwcLeac6/P1fzS2LFjlZmZ6UxHjhwp7uEAAAAAAPC7eXtqw7m5uerXr5+MMZo1a5anduPw9fWVr6+vx/cDAAAAAMDv4ZEgfi6Ef/vtt1q7dq3bb+MjIiKUlpbmVp+Xl6f09HRFREQ4NampqW41516fqwEAAAAAoCwq9p+mnwvh+/bt0+rVq1W1alW35dHR0crIyFBSUpIzb+3atSooKFDbtm2dmg0bNig3N9epWbVqlRo0aKCQkJDibhkAAAAAAGsuO4ifPHlSO3fu1M6dOyVJBw8e1M6dO3X48GHl5ubqrrvu0meffaYFCxYoPz9fKSkpSklJ0dmzZyVJjRo1UteuXTVkyBBt27ZNmzZt0rBhw9S/f39FRkZKku699175+Pho8ODB2rNnjxYtWqTp06dr5MiRxTdyAAAAAABKwGU/vmzdunW6+eabL5gfFxenp59+WnXr1i10vU8++USdO3eWJKWnp2vYsGFatmyZvLy81KdPH82YMUOVK1d26r/44gvFx8dr+/btqlatmoYPH64xY8YUuc+i3ja+NOLxZfbx+DIAAAAAv1dRc+jveo54aUYQx+UgiAMAAAD4vUrNc8QBAAAAAMD/EMQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQB1DubNiwQT169FBkZKRcLpeWLFnittwYo/Hjx6tGjRry9/dXTEyM9u3b51aTnp6uAQMGKDAwUMHBwRo8eLBOnjx5wXamTp2q+vXry9fXV1dddZWeffZZTw8PAAAApRxBHEC5k52drebNm2vmzJmFLp8yZYpmzJih2bNna+vWrQoICFBsbKzOnDnj1AwYMEB79uzRqlWrtHz5cm3YsEFDhw51284jjzyiN954Q1OnTtVXX32lpUuXqk2bNh4dGwAAAEo/lzHGlHQTnpCVlaWgoCBlZmYqMDCwpNu5LHWe+KCkWyh3Dk3uXtItoIS4XC4tXrxYvXr1kvTzWezIyEg99thjevzxxyVJmZmZCg8P17x589S/f3/t3btXjRs31vbt29WqVStJ0ooVK9StWzcdPXpUkZGR2rt3r5o1a6bdu3erQYMGJTU8AAAAWFTUHMoZcQA4z8GDB5WSkqKYmBhnXlBQkNq2bavExERJUmJiooKDg50QLkkxMTHy8vLS1q1bJUnLli3T1VdfreXLl6tu3bqqU6eO/vSnPyk9Pd3ugAAAAFDqEMQB4DwpKSmSpPDwcLf54eHhzrKUlBSFhYW5Lff29lZoaKhT88033+jbb7/Vu+++qzfffFPz5s1TUlKS7rrrLgujAAAAQGnmXdINAMCVqKCgQDk5OXrzzTdVv359SdKcOXPUsmVLJScn83N1AACAcowz4gBwnoiICElSamqq2/zU1FRnWUREhNLS0tyW5+XlKT093ampUaOGvL29nRAuSY0aNZIkHT582GP9AwAAoPQjiAPAeerWrauIiAitWbPGmZeVlaWtW7cqOjpakhQdHa2MjAwlJSU5NWvXrlVBQYHatm0rSerQoYPy8vJ04MABp+brr7+WJNWuXdvGUAAAAFBKXXYQt/X83S+++EI33nij/Pz8FBUVpSlTplz+6ACgECdPntTOnTu1c+dOST/foG3nzp06fPiwXC6XRowYoWeeeUZLly7Vrl27dN999ykyMtK5s3qjRo3UtWtXDRkyRNu2bdOmTZs0bNgw9e/fX5GRkZJ+vnnbDTfcoEGDBmnHjh1KSkrSn//8Z912221uZ8kBAABQ/lz2NeLnnr87aNAg9e7d+4Ll556/O3/+fNWtW1fjxo1TbGysvvzyS/n5+Un6+fm7x48f16pVq5Sbm6sHHnhAQ4cO1cKFCyX9fPapS5cuiomJ0ezZs7Vr1y4NGjRIwcHBFzynF0DZVJKP6Ttz+AulvvVX5/XIkSMlSQHX3apq3R+VMU1kGnfVH+6NU8GZbPnVbKzQLk+o4dP/O0ueXz9O6d/OVrsbO0tyqVKD9vo0orfbuPLaPaKvVr+qlu06yFXRV/51Wymk7aASGzuP6QMAACgdftdzxD31/N1Zs2bpb3/7m1JSUuTj4yNJeuKJJ7RkyRJ99dVXhfaSk5OjnJwc53VWVpaioqJ4jjiKhIBiH8e5fRznAAAAnlUizxEvrufvJiYm6qabbnJCuCTFxsYqOTlZP/30U6H7TkhIUFBQkDNFRUUV59AAAAAAACgWxRrEi+v5uykpKYVu4/x9/NLYsWOVmZnpTEeOHPn9AwIAAAAAoJhdMc8R9/X1la+vb0m3AQAAAADAJRXrGfHiev5uREREods4fx8AAAAAAJRFxRrEi+v5u9HR0dqwYYNyc3OdmlWrVqlBgwYKCQkpzpYBAAAAALDqsoO4jefv3nvvvfLx8dHgwYO1Z88eLVq0SNOnT3ceMQQAAAAAQFl12deIf/bZZ7r55pud1+fCcVxcnObNm6fRo0crOztbQ4cOVUZGhjp27KgVK1Y4zxCXpAULFmjYsGG69dZb5eXlpT59+mjGjBnO8qCgIK1cuVLx8fFq2bKlqlWrpvHjx/MMcQAAAABAmfe7niNemhX1+W2lEc9Xto/nK9vHcW4fxzkAAIBnlchzxAEAAAAAwKURxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIuKPYjn5+dr3Lhxqlu3rvz9/XXNNddo0qRJMsY4NcYYjR8/XjVq1JC/v79iYmK0b98+t+2kp6drwIABCgwMVHBwsAYPHqyTJ08Wd7sAAAAAAFhV7EH8+eef16xZs/Tyyy9r7969ev755zVlyhT94x//cGqmTJmiGTNmaPbs2dq6dasCAgIUGxurM2fOODUDBgzQnj17tGrVKi1fvlwbNmzQ0KFDi7tdAAAAAACs8i7uDW7evFk9e/ZU9+7dJUl16tTRW2+9pW3btkn6+Wz4tGnT9OSTT6pnz56SpDfffFPh4eFasmSJ+vfvr71792rFihXavn27WrVqJUn6xz/+oW7dumnq1KmKjIws7rYBAAAAALCi2M+It2/fXmvWrNHXX38tSfrvf/+rTz/9VLfffrsk6eDBg0pJSVFMTIyzTlBQkNq2bavExERJUmJiooKDg50QLkkxMTHy8vLS1q1bC91vTk6OsrKy3CYAAAAAAEqbYj8j/sQTTygrK0sNGzZUhQoVlJ+fr2effVYDBgyQJKWkpEiSwsPD3dYLDw93lqWkpCgsLMy9UW9vhYaGOjW/lJCQoAkTJhT3cAAAAAAAKFbFfkb8nXfe0YIFC7Rw4UJ9/vnnmj9/vqZOnar58+cX967cjB07VpmZmc505MgRj+4PAAAAAIDfotjPiI8aNUpPPPGE+vfvL0lq2rSpvv32WyUkJCguLk4RERGSpNTUVNWoUcNZLzU1VS1atJAkRUREKC0tzW27eXl5Sk9Pd9b/JV9fX/n6+hb3cAAAAAAAKFbFfkb81KlT8vJy32yFChVUUFAgSapbt64iIiK0Zs0aZ3lWVpa2bt2q6OhoSVJ0dLQyMjKUlJTk1Kxdu1YFBQVq27ZtcbcMAAAAAIA1xX5GvEePHnr22WdVq1YtNWnSRDt27NCLL76oQYMGSZJcLpdGjBihZ555Rtdee63q1q2rcePGKTIyUr169ZIkNWrUSF27dtWQIUM0e/Zs5ebmatiwYerfvz93TAcAAAAAlGnFHsT/8Y9/aNy4cfrLX/6itLQ0RUZG6s9//rPGjx/v1IwePVrZ2dkaOnSoMjIy1LFjR61YsUJ+fn5OzYIFCzRs2DDdeuut8vLyUp8+fTRjxozibhcAAAAAAKtcxhhT0k14QlZWloKCgpSZmanAwMCSbuey1Hnig5Juodw5NLl7SbdQ7nCc28dxDgAA4FlFzaHFfo04AAAAAAC4OII4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBACgHnn76ablcLrepYcOGzvIDBw7oD3/4g6pXr67AwED169dPqampbtv4+uuv1bNnT1WrVk2BgYHq2LGjPvnkE9tDAQCgzCOIAwBQTjRp0kTHjx93pk8//VSSlJ2drS5dusjlcmnt2rXatGmTzp49qx49eqigoMBZ/4477lBeXp7Wrl2rpKQkNW/eXHfccYdSUlJKakgAAJRJ3iXdAAAAsMPb21sREREXzN+0aZMOHTqkHTt2KDAwUJI0f/58hYSEaO3atYqJidEPP/ygffv2ac6cOWrWrJkkafLkyXrllVe0e/fuQrcLAAAKxxlxAADKiX379ikyMlJXX321BgwYoMOHD0uScnJy5HK55Ovr69T6+fnJy8vLOWtetWpVNWjQQG+++aays7OVl5enV199VWFhYWrZsmWJjAcAgLKKIA4AQDnQtm1bzZs3TytWrNCsWbN08OBB3XjjjTpx4oTatWungIAAjRkzRqdOnVJ2drYef/xx5efn6/jx45Ikl8ul1atXa8eOHapSpYr8/Pz04osvasWKFQoJCSnh0QEAULZ4JIh/9913+uMf/6iqVavK399fTZs21WeffeYsN8Zo/PjxqlGjhvz9/RUTE6N9+/a5bSM9PV0DBgxQYGCggoODNXjwYJ08edIT7QIAcMW7/fbb1bdvXzVr1kyxsbH68MMPlZGRoXfeeUfVq1fXu+++q2XLlqly5coKCgpSRkaGbrjhBnl5/fxPBWOM4uPjFRYWpo0bN2rbtm3q1auXevTo4YR1AABQNMUexH/66Sd16NBBFStW1EcffaQvv/xSf//7392+LZ8yZYpmzJih2bNna+vWrQoICFBsbKzOnDnj1AwYMEB79uzRqlWrtHz5cm3YsEFDhw4t7nYBACiXgoODVb9+fe3fv1+S1KVLFx04cEBpaWn64Ycf9H//93/67rvvdPXVV0uS1q5dq+XLl+vtt99Whw4ddMMNN+iVV16Rv7+/5s+fX5JDAQCgzCn2m7U9//zzioqK0ty5c515devWdf7bGKNp06bpySefVM+ePSVJb775psLDw7VkyRL1799fe/fu1YoVK7R9+3a1atVKkvSPf/xD3bp109SpUxUZGVncbQMAUK6cPHlSBw4c0MCBA93mV6tWTdLPwTstLU133nmnJOnUqVOS5JwhP8fLy8vtzuoAAODXFfsZ8aVLl6pVq1bq27evwsLCdP311+v11193lh88eFApKSmKiYlx5gUFBalt27ZKTEyUJCUmJio4ONgJ4ZIUExMjLy8vbd26tdD95uTkKCsry20CAAA/e/zxx7V+/XodOnRImzdv1h/+8AdVqFBB99xzjyRp7ty52rJliw4cOKB//etf6tu3rx599FE1aNBAkhQdHa2QkBDFxcXpv//9r77++muNGjVKBw8eVPfu3UtyaAAAlDnFfkb8m2++0axZszRy5Ej99a9/1fbt2/Xwww/Lx8dHcXFxzrNGw8PD3dYLDw93lqWkpCgsLMy9UW9vhYaGXvRZpQkJCZowYUJxDwcAgN+szhMflHQLju8/2KZpr85V/uksVfAPkm/NxgrunaDWf98mSfpp3Yc6uXukCk6flHdQmKq0+IP+7X2z3jtvDBW7P6kPN7ypJe1ulCnIU8VqtRTS82/q+dZR6a2jJTU0N4cm86UAAKD0K/YgXlBQoFatWum5556TJF1//fXavXu3Zs+erbi4uOLenWPs2LEaOXKk8zorK0tRUVEe2x8AAGVJ9Z5jLrk8pPP9Cul8/yVrfGtcq/C7JxVjVwAAlE/F/tP0GjVqqHHjxm7zGjVq5DyrNCIiQpKUmprqVpOamuosi4iIUFpamtvyvLw8paenOzW/5Ovrq8DAQLcJAAAAAIDSptiDeIcOHZScnOw27+uvv1bt2rUl/XzjtoiICK1Zs8ZZnpWVpa1btyo6OlrSz9ehZWRkKCkpyalZu3atCgoK1LZt2+JuGQAAAAAAa4r9p+mPPvqo2rdvr+eee079+vXTtm3b9Nprr+m1116TJLlcLo0YMULPPPOMrr32WtWtW1fjxo1TZGSkevXqJennM+hdu3bVkCFDNHv2bOXm5mrYsGHq378/d0wHAAAAAJRpxR7EW7durcWLF2vs2LGaOHGi6tatq2nTpmnAgAFOzejRo5Wdna2hQ4cqIyNDHTt21IoVK+Tn5+fULFiwQMOGDdOtt94qLy8v9enTRzNmzCjudgEAAAAAsKrYg7gk3XHHHbrjjjsuutzlcmnixImaOHHiRWtCQ0O1cOFCT7QHAAAAAECJKfZrxAEAAAAAwMURxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWOTxID558mS5XC6NGDHCmXfmzBnFx8eratWqqly5svr06aPU1FS39Q4fPqzu3burUqVKCgsL06hRo5SXl+fpdgEAAAAA8CiPBvHt27fr1VdfVbNmzdzmP/roo1q2bJneffddrV+/XseOHVPv3r2d5fn5+erevbvOnj2rzZs3a/78+Zo3b57Gjx/vyXYBAAAAAPA4jwXxkydPasCAAXr99dcVEhLizM/MzNScOXP04osv6pZbblHLli01d+5cbd68WVu2bJEkrVy5Ul9++aX+9a9/qUWLFrr99ts1adIkzZw5U2fPnvVUywAAAAAAeJzHgnh8fLy6d++umJgYt/lJSUnKzc11m9+wYUPVqlVLiYmJkqTExEQ1bdpU4eHhTk1sbKyysrK0Z8+eQveXk5OjrKwstwkAAAAAgNLG2xMbffvtt/X5559r+/btFyxLSUmRj4+PgoOD3eaHh4crJSXFqTk/hJ9bfm5ZYRISEjRhwoRi6B4AAAAAAM8p9jPiR44c0SOPPKIFCxbIz8+vuDd/UWPHjlVmZqYzHTlyxNq+AQAAAAAoqmIP4klJSUpLS9MNN9wgb29veXt7a/369ZoxY4a8vb0VHh6us2fPKiMjw2291NRURURESJIiIiIuuIv6udfnan7J19dXgYGBbhMAAAAAAKVNsQfxW2+9Vbt27dLOnTudqVWrVhowYIDz3xUrVtSaNWucdZKTk3X48GFFR0dLkqKjo7Vr1y6lpaU5NatWrVJgYKAaN25c3C0DAAAAAGBNsV8jXqVKFV133XVu8wICAlS1alVn/uDBgzVy5EiFhoYqMDBQw4cPV3R0tNq1aydJ6tKlixo3bqyBAwdqypQpSklJ0ZNPPqn4+Hj5+voWd8sAAAAAAFjjkZu1/ZqXXnpJXl5e6tOnj3JychQbG6tXXnnFWV6hQgUtX75cDz30kKKjoxUQEKC4uDhNnDixJNoFAAAAAKDYWAni69atc3vt5+enmTNnaubMmRddp3bt2vrwww893BkAAAAAAHZ57DniAAAAAADgQgRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWFXsQT0hIUOvWrVWlShWFhYWpV69eSk5Odqs5c+aM4uPjVbVqVVWuXFl9+vRRamqqW83hw4fVvXt3VapUSWFhYRo1apTy8vKKu10AAAAAAKwq9iC+fv16xcfHa8uWLVq1apVyc3PVpUsXZWdnOzWPPvqoli1bpnfffVfr16/XsWPH1Lt3b2d5fn6+unfvrrNnz2rz5s2aP3++5s2bp/Hjxxd3uwAAAAAAWOVd3BtcsWKF2+t58+YpLCxMSUlJuummm5SZmak5c+Zo4cKFuuWWWyRJc+fOVaNGjbRlyxa1a9dOK1eu1JdffqnVq1crPDxcLVq00KRJkzRmzBg9/fTT8vHxuWC/OTk5ysnJcV5nZWUV99AAAAAAAPjdPH6NeGZmpiQpNDRUkpSUlKTc3FzFxMQ4NQ0bNlStWrWUmJgoSUpMTFTTpk0VHh7u1MTGxiorK0t79uwpdD8JCQkKCgpypqioKE8NCQAAAACA38yjQbygoEAjRoxQhw4ddN1110mSUlJS5OPjo+DgYLfa8PBwpaSkODXnh/Bzy88tK8zYsWOVmZnpTEeOHCnm0QAAAAAA8PsV+0/TzxcfH6/du3fr008/9eRuJEm+vr7y9fX1+H4AAAAAAPg9PHZGfNiwYVq+fLk++eQT1axZ05kfERGhs2fPKiMjw60+NTVVERERTs0v76J+7vW5GgAAAAAAyqJiD+LGGA0bNkyLFy/W2rVrVbduXbflLVu2VMWKFbVmzRpnXnJysg4fPqzo6GhJUnR0tHbt2qW0tDSnZtWqVQoMDFTjxo2Lu2UAAAAAAKwp9p+mx8fHa+HChXr//fdVpUoV55ruoKAg+fv7KygoSIMHD9bIkSMVGhqqwMBADR8+XNHR0WrXrp0kqUuXLmrcuLEGDhyoKVOmKCUlRU8++aTi4+P5+TkAAAAAoEwr9iA+a9YsSVLnzp3d5s+dO1f333+/JOmll16Sl5eX+vTpo5ycHMXGxuqVV15xaitUqKDly5froYceUnR0tAICAhQXF6eJEycWd7sAAAAAAFhV7EHcGPOrNX5+fpo5c6Zmzpx50ZratWvrww8/LM7WAAAAAAAocR5/jjgAAAAAAPgfgjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAAAAFhEEAcAAAAAwCKCOAAAAAAAFhHEAQAAAACwiCAOAAAAAIBFBHEAAAAAACwiiAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gAAAAAAWEQQBwAAAADAIoI4AAAAAAAWEcQBAAAAALCIIA4AAAAAgEUEcQAAAAAALCKIAwAAAABgEUEcAAAAAACLCOIAAAC4Is2aNUvNmjVTYGCgAgMDFR0drY8++shZfubMGcXHx6tq1aqqXLmy+vTpo9TU1BLsGEB5QRAHAADAFalmzZqaPHmykpKS9Nlnn+mWW25Rz549tWfPHknSo48+qmXLlundd9/V+vXrdezYMfXu3buEuwYuT0JCglq3bq0qVaooLCxMvXr1UnJysltNSkqKBg4cqIiICAUEBOiGG27Qe++9V0IdQyKIAwAA4ArVo0cPdevWTddee63q16+vZ599VpUrV9aWLVuUmZmpOXPm6MUXX9Qtt9yili1bau7cudq8ebO2bNlS0q0DRbZ+/XrFx8dry5YtWrVqlXJzc9WlSxdlZ2c7Nffdd5+Sk5O1dOlS7dq1S71791a/fv20Y8eOEuy8fCOIAwAA4IqXn5+vt99+W9nZ2YqOjlZSUpJyc3MVExPj1DRs2FC1atVSYmJiCXYKXJ4VK1bo/vvvV5MmTdS8eXPNmzdPhw8fVlJSklOzefNmDR8+XG3atNHVV1+tJ598UsHBwW41sIsgDgAAgCvWrl27VLlyZfn6+urBBx/U4sWL1bhxY6WkpMjHx0fBwcFu9eHh4UpJSSmZZoFikJmZKUkKDQ115rVv316LFi1Senq6CgoK9Pbbb+vMmTPq3LlzCXUJ75JuAAAAAPCUBg0aaOfOncrMzNS///1vxcXFaf369SXdFuARBQUFGjFihDp06KDrrrvOmf/OO+/o7rvvVtWqVeXt7a1KlSpp8eLFqlevXgl2W74RxAEAAHDF8vHxccJGy5YttX37dk2fPl133323zp49q4yMDLez4qmpqYqIiCihboHfJz4+Xrt379ann37qNn/cuHHKyMjQ6tWrVa1aNS1ZskT9+vXTxo0b1bRp0xLqtnwjiAMAAKDcKCgoUE5Ojlq2bKmKFStqzZo16tOnjyQpOTlZhw8fVnR0dAl3CVy+YcOGafny5dqwYYNq1qzpzD9w4IBefvll7d69W02aNJEkNW/eXBs3btTMmTM1e/bskmq5XCOIAwAA4Io0duxY3X777apVq5ZOnDihhQsXat26dfr4448VFBSkwYMHa+TIkQoNDVVgYKCGDx+u6OhotWvXrqRbB4rMGKPhw4dr8eLFWrdunerWreu2/NSpU5IkLy/324NVqFBBBQUF1vqEO4I4AAAAfrM6T3xQ0i1c1A8fJumFV/6p/Ox0efkGyKd6HVXvO1FD1pyV1nwgE9BF6VWPKKbbnTL5ufKre4Oq3vaXUj0mSTo0uXtJt4BSJD4+XgsXLtT777+vKlWqODcbDAoKkr+/vxo2bKh69erpz3/+s6ZOnaqqVatqyZIlWrVqlZYvX17C3ZdfBHEAAABckap1e+SSy13ePqra5SFV7fKQpY5QVpXmL2e+nTVLki64A3rVbiNUuenPj+fLvXmUktbPV/TNsTK5p+UdXEOh3R7VXzYYaUPpHNuV/oUTQRwAAAAAyqjaY379rHbF0KtU/Q9/tdANiorniAMAAAAAYBFBHAAAAAAAiwjiAAAAAABYVKqD+MyZM1WnTh35+fmpbdu22rZtW0m3BAAAAADA71Jqg/iiRYs0cuRIPfXUU/r888/VvHlzxcbGKi0traRbAwAAAADgNyu1QfzFF1/UkCFD9MADD6hx48aaPXu2KlWqpH/+858l3RoAAAAAAL9ZqXx82dmzZ5WUlKSxY8c687y8vBQTE6PExMRC18nJyVFOTo7zOjMzU5KUlZXl2WY9oCDnVEm3UO6UxeOkrOM4t4/j3D6Oc/s4zu3jOLeP49w+jnP7yupxfq5vY8wl60plEP/hhx+Un5+v8PBwt/nh4eH66quvCl0nISFBEyZMuGB+VFSUR3rElSVoWkl3AHgexznKA45zlAcc5ygPyvpxfuLECQUFBV10eakM4r/F2LFjNXLkSOd1QUGB0tPTVbVqVblcrhLsrPzIyspSVFSUjhw5osDAwJJuB/AIjnOUBxznKA84zlEecJzbZ4zRiRMnFBkZecm6UhnEq1WrpgoVKig1NdVtfmpqqiIiIgpdx9fXV76+vm7zgoODPdUiLiEwMJAPOq54HOcoDzjOUR5wnKM84Di361Jnws8plTdr8/HxUcuWLbVmzRpnXkFBgdasWaPo6OgS7AwAAAAAgN+nVJ4Rl6SRI0cqLi5OrVq1Ups2bTRt2jRlZ2frgQceKOnWAAAAAAD4zUptEL/77rv1/fffa/z48UpJSVGLFi20YsWKC27ghtLD19dXTz311AWXCABXEo5zlAcc5ygPOM5RHnCcl14u82v3VQcAAAAAAMWmVF4jDgAAAADAlYogDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAItK7ePLUHrl5ubqcm627+XlJW9vDjWULY888oi+//77Itdfc801mjRpkgc7AgAAwJWCx5fhstWvX181a9b81TDucrlkjFF2dra2bdtmqTugeDRv3lxLly4tUq0xRv369eM4R5nz1ltv6cSJE0WuDwsLU69evTzXEOABffr00fHjx4tc37hxY73xxhse7AgofhznZQ+nKXHZAgICtHbt2iLXt27d2oPdAJ7h5eWl2rVrF7me7zRRFj377LMaPXp0kY/f5557jiCOMuebb77Rjh07ilzfpk0bD3YDeAbHedlDEMdlc7lcHq0HSgOOc5QHFStW1H333Vfk+pdfftmD3QCewf+fUR5wnJc93KwNAIByii+cAAAoGQRxAAAAAAAs4qfpAFCI06dPa+LEiUWq5fpwAAAAXA6COC6bj4+P2rdvX+T6atWqebAbwDNeffVVnT59usj1sbGxHuwG8Izc3Fxt2LChSLXGGL50QpmUnZ2tQYMGFamW4xxlFcd52UMQx2Vr06bNZT1fuV69eh7sBvCMm266qaRbADxu4MCB+uijj4pcf//993uuGcBDPvroI+Xm5ha53t/f34PdAJ7BcV728BxxXLYWLVpo6dKlRf4mrW/fvjxfGQBKodzc3Ms6K+Ll5SVvb77DR9ny1ltv6cSJE0WuDwsL4zF9KHM4zssegjgu2/XXX39Zzyls3bq1tm/f7sGOAAC/Rf369VWzZs0i1RpjdOrUKW3dutXDXQHF67rrrtPo0aOL/KXTzJkzOYGAMofjvOzha21cNh53AwBXhoCAAK1du7bI9a1bt/ZgN4BnVKxYUffdd1+R619++WUPdgN4Bsd52cPjywAAKKf4YhXlAcc5ygOO87KHIA4AAAAAgEX8NB2XjecrAwAAAMBvRxDHZeP5ygAAoKzIzc3Vhg0bilTL85VRVnGclz0EcVw2nq8MAFcGHx8ftW/fvsj11apV82A3gGcMHDhQH330UZHr77//fs81A3gIx3nZw+PLAAAopx5++GF9//33Ra6vV6+eJk2a5MGOgOKXm5t7WWf/vLy85O3NuSqULRznZQ9BHACAcqpFixZaunRpkf/x1rdvX547izKnfv36qlmzZpFqjTE6deqUtm7d6uGugOLFcV728DUIAADllMvlUq1atYpcz3f3KIsCAgK0du3aIte3bt3ag90AnsFxXvbw+DIAAMopnjuL8oDjHOUBx3nZQxAHAAAAAMAigjgAAAAAABZxjTgAAOXU6dOnNXHixCLVcn04AADFhyAOAEA59eqrr+r06dNFro+NjfVgN4Bn+Pj4qH379kWur1atmge7ATyD47zsIYgDAFBO3XTTTSXdAuBxbdq00ffff1/k+nr16nmwG8AzOM7LHp4jDgAAgCtWixYttHTp0iJfXtG3b19t27bNw10BxYvjvOzhjDgAAACuWC6XS7Vq1SpyPeeoUBZxnJc93DUdAAAAVyyer4zygOO87CGIAwAAAABgEUEcAAAAAACLuEYcAAAAV6zTp09r4sSJRarlulmUVRznZQ93TQcAAMAVa8OGDTp9+nSR64OCgtSuXTsPdgQUP47zsocgDgAAAACARVwjDgAAAACARQRxAAAAAAAsIogDAAAAAGARQRwAAAAAAIsI4gDgIZ07d9aIESNKuo2LqlOnjqZNm1ZmtlucXC6XlixZUtJteMTTTz+tFi1aFOs2Dx06JJfLpZ07dxbrdsuSefPmKTg42KP78MR7V5gr+fgHgLKCIA4AHvKf//xHkyZNKlJtWQ868+fPV8eOHSVJ27dv19ChQ4u87rp16+RyuZSRkeGh7jzj9ddf14033qiQkBCFhIQoJiZG27ZtK/L6999/v1wul9vUtWvXS64zb968C9Y5N6Wlpf3eIXlcUb+cOnPmjO6//341bdpU3t7e6tWrl8d7K0+OHz+u22+/vcj1l/MlxJ///Gddc8018vf3V/Xq1dWzZ0999dVXzvIff/xRXbt2VWRkpHx9fRUVFaVhw4YpKyvLqSnss+FyudSkSROnJiEhQa1bt1aVKlUUFhamXr16KTk5uchjAoCSRhAHAA8JDQ1VlSpVrO83NzfX+j7ff/993XnnnZKk6tWrq1KlStZ7MMYoLy/P2v7WrVune+65R5988okSExMVFRWlLl266LvvvivyNrp27arjx48701tvvXXJ+rvvvtut/vjx44qNjVWnTp0UFhb2e4dUauTn58vf318PP/ywYmJiSrqdK05ERIR8fX09su2WLVtq7ty52rt3rz7++GMZY9SlSxfl5+dLkry8vNSzZ08tXbpUX3/9tebNm6fVq1frwQcfdLYxffp0t2P8yJEjCg0NVd++fZ2a9evXKz4+Xlu2bNGqVauUm5urLl26KDs72yPjAoBiZwAAHtGpUyfzyCOPGGOMqV27tnn22WfNAw88YCpXrmyioqLMq6++6tRKcps6derkLHv99ddNw4YNja+vr2nQoIGZOXOms+zgwYNGknn77bfNTTfdZHx9fc3cuXNNXFyc6dmzp3nhhRdMRESECQ0NNX/5y1/M2bNnnXVr165tXnrpJbceZs+ebbp37278/f1Nw4YNzebNm82+fftMp06dTKVKlUx0dLTZv3+/2zhPnz5tAgICzN69ey+63ddff9306tXL+Pv7m3r16pn333/frf/zp7i4OGOMMfn5+ea5554zderUMX5+fqZZs2bm3Xffdbb7ySefGEnmww8/NDfccIOpWLGi+eSTT0ynTp3M8OHDzahRo0xISIgJDw83Tz31lFvPkszixYvdeli0aJHp2LGj8fPzM61atTLJyclm27ZtpmXLliYgIMB07drVpKWlXfT9zsvLM1WqVDHz58+/aM35zr1Hv0daWpqpWLGiefPNN515Tz31lGnevLmZPXu2qVmzpvH39zd9+/Y1GRkZl9xWfn6+ef75580111xjfHx8TFRUlHnmmWeMMf/7G7333numc+fOxt/f3zRr1sxs3rzZWf+HH34w/fv3N5GRkcbf399cd911ZuHChW7j/eV7ffDgwV8d48X+TufGOWfOHBMVFWUCAgLMQw89ZPLy8szzzz9vwsPDTfXq1Z0xFMVPP/1khg4dasLCwoyvr69p0qSJWbZsmTHGmLlz55qgoCCzYsUK07BhQxMQEGBiY2PNsWPH3LZxqc+rMcYcOXLE9O/f34SEhJhKlSqZli1bmi1btriN6Zz9+/ebunXrmvj4eFNQUOD0sHjxYlOvXj3j6+trunTpYg4fPuy2j1deecVcffXVpmLFiqZ+/fpux4cxhR//F3tvz33Ozp9++Xm6lP/+979G0gX/3zjf9OnTTc2aNS+6fPHixcblcplDhw5dtCYtLc1IMuvXry9ybwBQkgjiAOAhvwzioaGhZubMmWbfvn0mISHBeHl5ma+++soYY8y2bduMJLN69Wpz/Phx8+OPPxpjjPnXv/5latSoYd577z3zzTffmPfee8+EhoaaefPmGWP+94/oOnXqODXHjh0zcXFxJjAw0Dz44INm7969ZtmyZaZSpUrmtddec/orLDBfddVVZtGiRSY5Odn06tXL1KlTx9xyyy1mxYoV5ssvvzTt2rUzXbt2dRvn8uXLTf369S+53Zo1a5qFCxeaffv2mYcffthUrlzZ/PjjjyYvL8+89957RpJJTk42x48fdwLjM888Yxo2bGhWrFhhDhw4YObOnWt8fX3NunXrjDH/CwjNmjUzK1euNPv37zc//vij6dSpkwkMDDRPP/20+frrr838+fONy+UyK1eudOvpl0Hk3L7OjbNly5amc+fO5tNPPzWff/65qVevnnnwwQcv+n5nZWUZPz8/J7j9mri4OBMUFGSqV69u6tevbx588EHzww8/FGndc6ZOnWqCgoLMqVOnnHlPPfWUCQgIMLfccovZsWOHWb9+valXr5659957L7mt0aNHm5CQEDNv3jyzf/9+s3HjRvP6668bY9z/RsuXLzfJycnmrrvuMrVr1za5ubnGGGOOHj1qXnjhBbNjxw5z4MABM2PGDFOhQgWzdetWY4wxGRkZJjo62gwZMsQcP37cHD9+3OTl5RXp73SxIF65cmVz1113mT179pilS5caHx8fExsba4YPH26++uor889//tNIcoLupeTn55t27dqZJk2amJUrV5oDBw6YZcuWmQ8//NAY83MQr1ixoomJiTHbt283SUlJplGjRm5/11/7vJ44ccJcffXV5sYbbzQbN240+/btM4sWLXJC7/lB/L///a+JiIgwf/vb35ztn+uhVatWZvPmzeazzz4zbdq0Me3bt3dq/vOf/5iKFSuamTNnmuTkZPP3v//dVKhQwaxdu9apudjxX9h7m5OTY6ZNm2YCAwOd9+3EiRO/+vc0xpiTJ0+aESNGmLp165qcnJxCa7777jvTqVMnM2DAgItu54477jC33XbbJfe1b98+I8ns2rWrSL0BQEkjiAOAh/wyiP/xj390lhUUFJiwsDAza9YsY8z//jG8Y8cOt21cc801bmcVjTFm0qRJJjo62m29adOmudXExcWZ2rVruwWdvn37mrvvvtt5XVhgfvLJJ53XiYmJRpKZM2eOM++tt94yfn5+bvsaMmSIefzxx4u83ZMnTxpJ5qOPPjLG/C9Q//TTT07NmTNnTKVKldzOuBpjzODBg80999zjtt6SJUvcajp16mQ6duzoNq9169ZmzJgxbj39Moi88cYbbuOUZNasWePMS0hIMA0aNDAX89BDD5mrr77anD59+qI153vrrbfM+++/b7744guzePFi06hRI9O6desihdNzGjVqZB566CG3eU899ZSpUKGCOXr0qDPvo48+Ml5eXub48eOFbicrK8v4+vo6wfuXCvsb7dmzx0hyfglRmO7du5vHHnvMeX3+Z6KoLhXEK1WqZLKyspx5sbGxpk6dOiY/P9+Z16BBA5OQkPCr+/n444+Nl5eXSU5OLnT53LlzLzizO3PmTBMeHu68/rXP66uvvmqqVKnifNFW2JiaN29uNm3aZEJCQszUqVML7eH8Lxb27t1rJDlfeLRv394MGTLEbb2+ffuabt26Oa9/7fj/5Xt77kx8Uc2cOdMEBAQYSaZBgwaFng3v37+/8ff3N5JMjx49Lvq5+e6770yFChXMokWLLrq//Px80717d9OhQ4ci9wgAJY1rxAHAkmbNmjn/7XK5FBERcckbbGVnZ+vAgQMaPHiwKleu7EzPPPOMDhw44FbbqlWrC9Zv0qSJKlSo4LyuUaPGr97Q6/wew8PDJUlNmzZ1m3fmzBnnxkrGGC1btsy5Prwo2w0ICFBgYOAle9m/f79OnTql2267zW3sb775ZpHGfv7+pOIb+8W2MXnyZL399ttavHix/Pz8Lrmfc/r3768777xTTZs2Va9evbR8+XJt375d69atkyTdfvvtzrjPv0nVOYmJidq7d68GDx58wbJatWrpqquucl5HR0eroKBAycnJ2rhxo9vfdMGCBdq7d69ycnJ06623XrLn8/9GNWrUkCTnb5Kfn69JkyapadOmCg0NVeXKlfXxxx/r8OHDl9xmkyZNnF4u5wZi0s936D//Pgzh4eFq3LixvLy83OYV5UZ2O3fuVM2aNVW/fv2L1lSqVEnXXHON8/r846oon9edO3fq+uuvV2ho6EX3cfjwYd12220aP368HnvssQuWe3t7q3Xr1s7rhg0bKjg4WHv37pUk7d27Vx06dHBbp0OHDs7yi7nUe1uY5557zm2c57/PAwYM0I4dO7R+/XrVr19f/fr105kzZ9zWf+mll/T555/r/fff14EDBzRy5MhC9zN//nwFBwdf8oZ98fHx2r17t95+++1LjhEAShPvkm4AAMqLihUrur12uVwqKCi4aP3Jkycl/Xx37rZt27otOz9gSz+H29+7v1+u43K5Ljrv3Ha2bdumvLw8tW/fvsjbLUov58b+wQcfuAVKSRfcZMrm2AvbxtSpUzV58mStXr36gi8ALsfVV1+tatWqaf/+/br11lv1xhtv6PTp04WOR5LeeOMNtWjRQi1btrys/bRq1crt7vzh4eE6dOhQkda91LHwwgsvaPr06Zo2bZqaNm2qgIAAjRgxQmfPnr3kNj/88EPnBoP+/v6XMZLC3+ff8t4Xdd+FbdsYI6lon9ei7KN69eqKjIzUW2+9pUGDBikwMPBX1ykOl3pvC/Pggw+qX79+zuvIyEjnv4OCghQUFKRrr71W7dq1U0hIiBYvXqx77rnHqYmIiFBERIQaNmyo0NBQ3XjjjRo3bpzzJYD08xd9//znPzVw4ED5+PgU2sewYcO0fPlybdiwQTVr1rz8gQNACSGIA0ApcO4fmefuLCz9HJAiIyP1zTffaMCAASXV2iW9//776t69+wVfDFyOwsbeuHFj+fr66vDhw+rUqdPv7tNTpkyZomeffVYff/xxoWfmL8fRo0f1448/OkHkl19AnO/kyZN65513lJCQUOjyw4cP69ixY0442rJli7y8vNSgQQP5+/urXr16bvXXXnut/P39tWbNGv3pT3/6Tf1v2rRJPXv21B//+EdJP4e4r7/+Wo0bN3ZqfHx83N5nSapdu/Zv2l9xa9asmY4ePaqvv/76kmfFL6Yon9dmzZrpjTfeUHp6+kXPivv7+2v58uXq1q2bYmNjtXLlSrez/nl5efrss8/Upk0bSVJycrIyMjLUqFEjSVKjRo20adMmxcXFOets2rTJ7X24XIW9b6GhoZc8s3+O+fkySOXk5Fy05lzg/2XN+vXrtX///kJ/9WGM0fDhw7V48WKtW7dOdevWLcpQAKDUIIgDQCkQFhYmf39/rVixQjVr1pSfn5+CgoI0YcIEPfzwwwoKClLXrl2Vk5Ojzz77TD/99NNFf8pp09KlSzVx4sTftY3atWvL5XI54cPf319VqlTR448/rkcffVQFBQXq2LGjMjMztWnTJgUGBrqFjJLy/PPPa/z48Vq4cKHq1KmjlJQUSXJ+qnspJ0+e1IQJE9SnTx9FRETowIEDGj16tOrVq6fY2Nhf3feiRYuUl5fnhN5f8vPzU1xcnKZOnaqsrCw9/PDD6tevnyIiIi5aP2bMGI0ePVo+Pj7q0KGDvv/+e+3Zs6fQEFSYa6+9Vv/+97+1efNmhYSE6MUXX1RqaqpbAKxTp462bt2qQ4cOqXLlygoNDXX7Gfn5vvzyS509e1bp6ek6ceKEcxa/RYsWRerncnXq1Ek33XST+vTpoxdffFH16tXTV199VaTnu5/za5/Xe+65R88995x69eqlhIQE1ahRQzt27FBkZKSio6Od7QQEBOiDDz7Q7bffrttvv10rVqxwjqmKFStq+PDhmjFjhry9vTVs2DC1a9fOCeajRo1Sv379dP311ysmJkbLli3Tf/7zH61evfo3/23q1KmjkydPas2aNWrevLkqVapU6CMKv/nmGy1atEhdunRR9erVdfToUU2ePFn+/v7q1q2bpJ9/AZGamqrWrVurcuXK2rNnj0aNGqUOHTqoTp06btubM2eO2rZtq+uuu+6CfcXHx2vhwoV6//33VaVKFefzFxQUdNm/rACAksA14gBQCnh7e2vGjBl69dVXFRkZqZ49e0qS/vSnP+mNN97Q3Llz1bRpU3Xq1Enz5s0rFWd/Dhw4oP379xcpOF7KVVddpQkTJuiJJ55QeHi4hg0bJkmaNGmSxo0bp4SEBDVq1Ehdu3bVBx98UCrGLkmzZs3S2bNnddddd6lGjRrONHXq1F9dt0KFCvriiy905513qn79+ho8eLBatmypjRs3Fun5znPmzFHv3r0VHBxc6PJ69eqpd+/e6tatm7p06aJmzZrplVdeueQ2x40bp8cee0zjx49Xo0aNdPfddxfp2upznnzySd1www2KjY1V586dFRERccF1vY8//rgqVKigxo0bq3r16pe8frxbt266/vrrtWzZMq1bt07XX3+9rr/++iL381u89957at26te655x41btxYo0ePvuBM8KX82ufVx8dHK1euVFhYmLp166amTZtq8uTJhf6ipHLlyvroo49kjFH37t2d52NXqlRJY8aM0b333qsOHTqocuXKWrRokbNer169NH36dE2dOlVNmjTRq6++qrlz56pz586/+e/Svn17Pfjgg7r77rtVvXp1TZkypdA6Pz8/bdy4Ud26dVO9evV09913q0qVKtq8ebPznHt/f3+9/vrr6tixoxo1aqRHH31Ud955p5YvX+62rczMTL333nsX/SJo1qxZyszMVOfOnd0+f+f/LQCgNHOZcxc3AQBwGV588UWtXr1aH374YUm3ApQL8+bN04gRI5SRkVHSrQAAfifOiAMAfpOaNWtq7NixJd0GAABAmUMQBwD8Jv369dONN95Y0m2USr98RNgvJ9i3YMGCi74fhT0eDgAAT+Kn6QAAFLPTp0/ru+++u+jyX961HJ534sQJpaamFrqsYsWKpebu7QCA8oEgDgAAAACARfw0HQAAAAAAiwjiAAAAAABYRBAHAAAAAMAigjgAAAAAABYRxAEAAAAAsIggDgAAAACARQRxAAAAAAAs+n9L58W9ZB+vmAAAAABJRU5ErkJggg==","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["for col in df.columns[5:]:\n","    print(\"*\" * 10, col, \"*\" * 10)\n","    print(df[col].value_counts())\n","    plot_value_counts(df, col)"]},{"cell_type":"code","execution_count":11,"metadata":{},"outputs":[],"source":["import re\n","\n","\n","def clean_up(df, model_name):\n","    df[model_name] = df[model_name].apply(\n","        lambda x: re.sub(r\"回答.*是\", \"是\", x)\n","        .replace(\"是男孩\", \"是\")\n","        .replace(\"。\", \"\")\n","        .strip()\n","    )\n","    return df"]},{"cell_type":"code","execution_count":12,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** internlm2_5-7b-chat-1m\n","(RTX 4080,4bit,P1) **********\n","results/mgtv-results_nv4080.csv\n","internlm/internlm2_5-7b-chat-1m\n","不是     1997\n","是       979\n","不重要      24\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm2_5-7b-chat-1m\n","(RTX 4080,bf16,P1) **********\n","results/mgtv-results_nv4080_r2.csv\n","internlm/internlm2_5-7b-chat-1m\n","不是     1670\n","是      1284\n","不重要      46\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm2_5-7b-chat-1m\n","(Tesla T4,4bit,P1) **********\n","results/mgtv-results_t4.csv\n","internlm/internlm2_5-7b-chat-1m\n","不是     1967\n","是      1008\n","不重要      25\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm2_5-7b-chat-1m\n","(Tesla T4,bf16,P1) **********\n","results/mgtv-results_t4_r2.csv\n","internlm/internlm2_5-7b-chat-1m\n","不是     1660\n","是      1291\n","不重要      49\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm2_5-7b-chat-1m\n","(Tesla T4,bf16,P2) **********\n","results/mgtv-results_t4_r3.csv\n","internlm/internlm2_5-7b-chat-1m\n","是       1358\n","不重要     1169\n","不是       472\n","问法错误       1\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["for row in df.itertuples():\n","    df2 = pd.read_csv(row.csv_file)\n","    df2 = clean_up(df2, row.model_name)\n","    print(\"*\" * 10, row.run, \"*\" * 10)\n","    print(row.csv_file)\n","    print(df2[row.model_name].value_counts())\n","    plot_value_counts(df2, row.model_name)"]},{"cell_type":"code","execution_count":16,"metadata":{},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n","\n","\n","def calc_metrics_for_csv(csv_file, model_name):\n","    df = pd.read_csv(csv_file)\n","    df = clean_up(df, model_name)\n","\n","    y_true = df[\"label\"]\n","    y_pred = df[model_name]\n","\n","    accuracy = accuracy_score(y_true, y_pred)\n","    precision = precision_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","    recall = recall_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","    f1 = f1_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","\n","    return accuracy, float(precision), float(recall), float(f1)"]},{"cell_type":"code","execution_count":17,"metadata":{},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>csv_file</th>\n","      <th>model_name</th>\n","      <th>run</th>\n","      <th>accuracy</th>\n","      <th>precision</th>\n","      <th>recall</th>\n","      <th>f1</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>results/mgtv-results_nv4080.csv</td>\n","      <td>internlm/internlm2_5-7b-chat-1m</td>\n","      <td>internlm2_5-7b-chat-1m\\n(RTX 4080,4bit,P1)</td>\n","      <td>0.740333</td>\n","      <td>0.731676</td>\n","      <td>0.761138</td>\n","      <td>0.731746</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>results/mgtv-results_nv4080_r2.csv</td>\n","      <td>internlm/internlm2_5-7b-chat-1m</td>\n","      <td>internlm2_5-7b-chat-1m\\n(RTX 4080,bf16,P1)</td>\n","      <td>0.759667</td>\n","      <td>0.741854</td>\n","      <td>0.781014</td>\n","      <td>0.758887</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>results/mgtv-results_t4.csv</td>\n","      <td>internlm/internlm2_5-7b-chat-1m</td>\n","      <td>internlm2_5-7b-chat-1m\\n(Tesla T4,4bit,P1)</td>\n","      <td>0.746667</td>\n","      <td>0.737058</td>\n","      <td>0.767649</td>\n","      <td>0.739094</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>results/mgtv-results_t4_r2.csv</td>\n","      <td>internlm/internlm2_5-7b-chat-1m</td>\n","      <td>internlm2_5-7b-chat-1m\\n(Tesla T4,bf16,P1)</td>\n","      <td>0.760000</td>\n","      <td>0.742271</td>\n","      <td>0.781357</td>\n","      <td>0.759572</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>results/mgtv-results_t4_r3.csv</td>\n","      <td>internlm/internlm2_5-7b-chat-1m</td>\n","      <td>internlm2_5-7b-chat-1m\\n(Tesla T4,bf16,P2)</td>\n","      <td>0.509333</td>\n","      <td>0.748183</td>\n","      <td>0.515346</td>\n","      <td>0.540619</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                             csv_file                       model_name  \\\n","0     results/mgtv-results_nv4080.csv  internlm/internlm2_5-7b-chat-1m   \n","1  results/mgtv-results_nv4080_r2.csv  internlm/internlm2_5-7b-chat-1m   \n","2         results/mgtv-results_t4.csv  internlm/internlm2_5-7b-chat-1m   \n","3      results/mgtv-results_t4_r2.csv  internlm/internlm2_5-7b-chat-1m   \n","4      results/mgtv-results_t4_r3.csv  internlm/internlm2_5-7b-chat-1m   \n","\n","                                          run  accuracy  precision    recall  \\\n","0  internlm2_5-7b-chat-1m\\n(RTX 4080,4bit,P1)  0.740333   0.731676  0.761138   \n","1  internlm2_5-7b-chat-1m\\n(RTX 4080,bf16,P1)  0.759667   0.741854  0.781014   \n","2  internlm2_5-7b-chat-1m\\n(Tesla T4,4bit,P1)  0.746667   0.737058  0.767649   \n","3  internlm2_5-7b-chat-1m\\n(Tesla T4,bf16,P1)  0.760000   0.742271  0.781357   \n","4  internlm2_5-7b-chat-1m\\n(Tesla T4,bf16,P2)  0.509333   0.748183  0.515346   \n","\n","         f1  \n","0  0.731746  \n","1  0.758887  \n","2  0.739094  \n","3  0.759572  \n","4  0.540619  "]},"execution_count":17,"metadata":{},"output_type":"execute_result"}],"source":["df[\"accuracy\"], df[\"precision\"], df[\"recall\"], df[\"f1\"] = zip(\n","    *df.apply(lambda x: calc_metrics_for_csv(x[\"csv_file\"], x[\"model_name\"]), axis=1)\n",")\n","df"]},{"cell_type":"code","execution_count":18,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1200x500 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# plot metrics for each model\n","import matplotlib.pyplot as plt\n","\n","fig, ax = plt.subplots(1, 1, figsize=(12, 5))\n","\n","df.plot(x=\"run\", y=[\"accuracy\", \"precision\", \"recall\", \"f1\"], kind=\"bar\", ax=ax)\n","\n","# add values on top of bars\n","for p in ax.patches:\n","    ax.annotate(\n","        f\"{p.get_height():.3f}\",\n","        (p.get_x() + p.get_width() / 2, p.get_height()),\n","        ha=\"center\",\n","        va=\"bottom\",\n","        fontsize=10,\n","    )\n","\n","# add title and labels\n","# ax.set_title(\"Metrics for different settings\")\n","# ax.set_ylabel(\"Value\")\n","ax.set_xlabel(\"Model (GPU, Precision, Prompt Template)\")\n","# rotate x labels\n","plt.xticks(rotation=0)\n","\n","# set legend at the right to avoid overlapping with bars\n","plt.legend(loc=\"center left\", bbox_to_anchor=(1.0, 0.5))\n","# plt.tight_layout()\n","\n","plt.show()"]}],"metadata":{"accelerator":"GPU","application/vnd.databricks.v1+notebook":{"dashboards":[],"environmentMetadata":null,"language":"python","notebookMetadata":{"pythonIndentUnit":4},"notebookName":"07_MAC_+_Qwen2-7B-Instructi_Unsloth_train","widgets":{}},"colab":{"gpuType":"T4","provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.9"}},"nbformat":4,"nbformat_minor":0}
+{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{},"inputWidgets":{},"nuid":"0ea8b46b-839b-445b-8043-ccdf4e920ace","showTitle":false,"title":""},"id":"YLH80COBzi_F"},"outputs":[],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":2,"metadata":{"id":"63B5exAuzq4M"},"outputs":[],"source":["from pathlib import Path\n","\n","try:\n","    from google.colab import drive\n","    drive.mount('/content/drive')\n","    workding_dir = \"/content/drive/MyDrive/logical-reasoning/\"\n","except ModuleNotFoundError:\n","    workding_dir = str(Path.cwd().parent)"]},{"cell_type":"code","execution_count":3,"metadata":{"executionInfo":{"elapsed":368,"status":"ok","timestamp":1719461634865,"user":{"displayName":"Donghao Huang","userId":"00463591218503521679"},"user_tz":-480},"id":"zFulf0bg0H-9","outputId":"debdd535-c828-40b9-efc0-8a180e5830dd"},"outputs":[{"name":"stdout","output_type":"stream","text":["workding dir: /Users/inflaton/Library/CloudStorage/GoogleDrive-dh.huang.2023@smu.edu.sg/My Drive/logical-reasoning\n"]}],"source":["import os\n","import sys\n","\n","os.chdir(workding_dir)\n","sys.path.append(workding_dir)\n","print(\"workding dir:\", workding_dir)"]},{"cell_type":"code","execution_count":4,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{},"inputWidgets":{},"nuid":"9f67ec60-2f24-411c-84eb-0dd664b44775","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":589,"status":"ok","timestamp":1719462011879,"user":{"displayName":"Donghao Huang","userId":"00463591218503521679"},"user_tz":-480},"id":"DIUiweYYzi_I","outputId":"e16e9247-9077-4b0c-f8ea-17059f05a1c4"},"outputs":[{"name":"stdout","output_type":"stream","text":["loading env vars from: /Users/inflaton/Library/CloudStorage/GoogleDrive-dh.huang.2023@smu.edu.sg/My Drive/logical-reasoning/.env\n"]},{"data":{"text/plain":["True"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["from dotenv import find_dotenv, load_dotenv\n","\n","found_dotenv = find_dotenv(\".env\")\n","\n","if len(found_dotenv) == 0:\n","    found_dotenv = find_dotenv(\".env.example\")\n","print(f\"loading env vars from: {found_dotenv}\")\n","load_dotenv(found_dotenv, override=True)"]},{"cell_type":"code","execution_count":11,"metadata":{},"outputs":[],"source":["import re\n","\n","\n","def clean_up(df, model_name):\n","    df[model_name] = df[model_name].apply(\n","        lambda x: re.sub(r\"回答.*是\", \"是\", x)\n","        .replace(\"是男孩\", \"是\")\n","        .replace(\"。\", \"\")\n","        .strip()\n","    )\n","    return df"]},{"cell_type":"code","execution_count":12,"metadata":{"id":"W2QyVreqhOGM","outputId":"68b9590e-1ac6-4c6f-e0c4-e273ec816419"},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>label</th>\n","      <th>title</th>\n","      <th>puzzle</th>\n","      <th>truth</th>\n","      <th>internlm/internlm2_5-7b-chat-1m</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-562</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-1124</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-1686</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-2248</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-2810</th>\n","      <th>internlm/internlm2_5-7b-chat-1m_checkpoint-3372</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>甄加索是自杀吗</td>\n","      <td>不是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>甄加索有身体上的疾病吗</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>画作是甄的</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>甄有心脏病吗</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>车轮是凶手留下的</td>\n","      <td>不是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>2995</th>\n","      <td>哭泣者必须在晚上祭奠吗</td>\n","      <td>是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","    </tr>\n","    <tr>\n","      <th>2996</th>\n","      <td>尸体在湖里吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>2997</th>\n","      <td>哭泣者和死者有特殊关系吗</td>\n","      <td>是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2998</th>\n","      <td>是帽子的主人去世了吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2999</th>\n","      <td>死者受伤了吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","      <td>不重要</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3000 rows × 12 columns</p>\n","</div>"],"text/plain":["              text label title  \\\n","0          甄加索是自杀吗    不是  海岸之谜   \n","1      甄加索有身体上的疾病吗     是  海岸之谜   \n","2            画作是甄的     是  海岸之谜   \n","3           甄有心脏病吗     是  海岸之谜   \n","4         车轮是凶手留下的    不是  海岸之谜   \n","...            ...   ...   ...   \n","2995   哭泣者必须在晚上祭奠吗     是  甄庄哭声   \n","2996        尸体在湖里吗    不是  甄庄哭声   \n","2997  哭泣者和死者有特��关系吗     是  甄庄哭声   \n","2998    是帽子的主人去世了吗    不是  甄庄哭声   \n","2999        死者受伤了吗    不是  甄庄哭声   \n","\n","                                                 puzzle  \\\n","0     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","1     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","2     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","3     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","4     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","...                                                 ...   \n","2995  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2996  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2997  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2998  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2999  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","\n","                                                  truth  \\\n","0     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","1     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","2     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","3     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","4     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","...                                                 ...   \n","2995  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2996  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2997  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2998  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2999  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","\n","     internlm/internlm2_5-7b-chat-1m  \\\n","0                                 不是   \n","1                                  是   \n","2                                 不是   \n","3                                  是   \n","4                                 不是   \n","...                              ...   \n","2995                              不是   \n","2996                              不是   \n","2997                               是   \n","2998                               是   \n","2999                              不是   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-562  \\\n","0                                                不是   \n","1                                                 是   \n","2                                                 是   \n","3                                                 是   \n","4                                               不重要   \n","...                                             ...   \n","2995                                            不重要   \n","2996                                            不重要   \n","2997                                              是   \n","2998                                              是   \n","2999                                            不重要   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-1124  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                             不重要   \n","2997                                               是   \n","2998                                               是   \n","2999                                             不重要   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-1686  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                              不是   \n","2997                                               是   \n","2998                                               是   \n","2999                                              不是   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-2248  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                              不是   \n","2997                                               是   \n","2998                                               是   \n","2999                                             不重要   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-2810  \\\n","0                                                 不是   \n","1                                                  是   \n","2                                                  是   \n","3                                                  是   \n","4                                                 不是   \n","...                                              ...   \n","2995                                             不重要   \n","2996                                              不是   \n","2997                                               是   \n","2998                                               是   \n","2999                                              不是   \n","\n","     internlm/internlm2_5-7b-chat-1m_checkpoint-3372  \n","0                                                 不是  \n","1                                                  是  \n","2                                                  是  \n","3                                                  是  \n","4                                                 不是  \n","...                                              ...  \n","2995                                             不重要  \n","2996                                              不是  \n","2997                                               是  \n","2998                                               是  \n","2999                                             不重要  \n","\n","[3000 rows x 12 columns]"]},"execution_count":12,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","df = pd.read_csv(\"results/mgtv-results_nv4080_r2.csv\")\n","df = clean_up(df, \"internlm/internlm2_5-7b-chat-1m\")\n","df"]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[],"source":["import matplotlib.pyplot as plt\n","from matplotlib import rcParams\n","\n","def plot_value_counts(df, column):\n","    font_family = rcParams[\"font.family\"]\n","    # Set the font to SimHei to support Chinese characters\n","    rcParams[\"font.family\"] = \"STHeiti\"\n","    rcParams[\"axes.unicode_minus\"] = False  # This is to support the minus sign in Chinese.\n","\n","    plt.figure(figsize=(12, 6))\n","    df[column].value_counts().plot(kind=\"bar\")\n","    # add values on top of bars\n","    for i, v in enumerate(df[column].value_counts()):\n","        plt.text(i, v + 0.1, str(v), ha=\"center\")\n","    plt.show()\n","    \n","    rcParams[\"font.family\"] = font_family\n"]},{"cell_type":"code","execution_count":7,"metadata":{},"outputs":[{"data":{"text/plain":["['text',\n"," 'label',\n"," 'title',\n"," 'puzzle',\n"," 'truth',\n"," 'internlm/internlm2_5-7b-chat-1m',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-562',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-1124',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-1686',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-2248',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-2810',\n"," 'internlm/internlm2_5-7b-chat-1m_checkpoint-3372']"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["df.columns.to_list()"]},{"cell_type":"code","execution_count":13,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m **********\n","internlm/internlm2_5-7b-chat-1m\n","不是     1670\n","是      1284\n","不重要      46\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA94AAAIoCAYAAACf0TObAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAABItElEQVR4nO3deXxU5d3//3dClpkEZgJhiZAECEskBLQtixVBFKgLSgggtkUbyyIUZG1dEIjeoAKuX2/FIigoW701IigiqCxlKUQqolBEI4QsKAECZAhkz/n9wY+pY8IizpVJyOv5eJwHnetznTOfE/CUN9eZM36WZVkCAAAAAABG+Pu6AQAAAAAArmQEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABgX4ugFvKS8v1/fff6969erJz8/P1+0AAAAAAK5wlmXp1KlTatq0qfz9z7+ufcUE7++//15RUVG+bgMAAAAAUMtkZWUpMjLyvPUrJnjXq1dP0tkTdjgcPu4GAAAAAHClc7lcioqKcufR87ligve528sdDgfBGwAAAABQZS72cWcergYAAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8gUuwbNkypaWl+boNAAAAADUQwRu13k033SR/f389++yzldYPHTqkiRMnKjAw0D3Wq1cvBQQEeGx+fn567733JEkul0tDhgxR3bp11bRpU82ePbtKzgUAAABA9UPwRq23YcMGJScnn7c+ceJETZw4US1atHCPrVu3TqWlpe5ty5Yt6tChg/r37y9Juv/++xUYGKhDhw5p27ZtSklJ0auvvmr4TAAAAABURwG+bgCoztatW6e9e/dq6dKlF5w3Y8YMTZkyRX5+fjp06JA2bNigjIwM2Ww2OZ1OLVq0SLfddptGjhxZRZ0DAAAAqC5Y8QbOo6SkROPGjdPf//53j9vMf2rnzp06cOCA7rrrLknS1q1b1adPH9lsNvecdu3aqW7dunxOHAAAAKiFCN7Aebz44ovav3+/7rrrLrVp00Yff/xxpfOeeOIJPfroo/L3P/ufU2Zmplq3bl1hXmxsrA4cOGC0ZwAAAADVD8EbqMTp06c1a9YszZkzR/v379czzzyjIUOG6IcffvCYt2fPHu3evVt//OMf3WMFBQUKCQmpcEy73a6CggLjvQMAAACoXgjeQCU+/vhj3XzzzRo2bJhCQ0PVv39/JSUlafHixR7znnzyST3yyCOqU6eOe8xut6uwsLDCMXNzcysN5AAAAACubARvoBLfffed4uPjPcY6duyojIwM9+u0tDSlpqbqT3/6k8e86OhopaenVzhmenq6YmJizDQMAAAAoNoieAOViIyM1J49ezzGdu/erZYtW7pfP/XUU/rb3/5W4cFr3bp1c3/d2Dl79uxRUVFRpZ/9BgAAAHBlI3gDlejXr59SU1P1+uuv68yZM3r//fe1bNkyJSUlSZIOHjyo9evXa9iwYRX2bdasma6//npNnDhR+fn5ysrK0ogRIzR16tSqPg0AAAAA1QDBG6hEaGio1q5dq0WLFikiIkKzZs3SqlWr1KhRI0nSl19+qcmTJys4OLjS/V999VUdP35cERER6tKliwYMGFBpSAcAAABw5fOzLMvydRPe4HK55HQ6lZeXJ4fD4et2aowWj3zo6xZQSxyc1dfXLQAAAABedak5lBVvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDjAXvZcuWKS0tzdThAQAAAACoES4reN90003y9/fXs88+W2n90KFDmjhxogIDAz3Gp0+friZNmsjhcGjo0KHKz89311wul4YMGaK6deuqadOmmj179uW0BgAAAABAtXJZwXvDhg1KTk4+b33ixImaOHGiWrRo4R6bO3euVqxYoe3btys7O1t+fn4aMWKEu37//fcrMDBQhw4d0rZt25SSkqJXX331ctoDAAAAAKDaCPD2AdetW6e9e/dq6dKlHuMvvPCCli1bppYtW0o6G8RbtWql/fv3y2azacOGDcrIyJDNZpPT6dSiRYt02223aeTIkd5uEQAAAACAKuPV4F1SUqJx48Zp7ty5HreZHzlyRKdPn9ZvfvMb91hgYKD69eun9evXy+l0qk+fPrLZbO56u3btVLduXaWlpalNmzbebBMAAAAAgCrj1Yervfjii9q/f7/uuusutWnTRh9//LEkKTMzU61bt64wPzY2VgcOHLhoHQAAAACAmsprK96nT5/WrFmzNGfOHP3+97/XJ598oiFDhuirr75SQUGBQkJCKuxjt9tVUFBw0XplioqKVFRU5H7tcrm8dSoAAAAAAHiN11a8P/74Y918880aNmyYQkND1b9/fyUlJWnx4sWy2+0qLCyssE9ubq5CQkIuWq/MzJkz5XQ63VtUVJS3TgUAAAAAAK/xWvD+7rvvFB8f7zHWsWNHZWRkKDo6Wunp6RX2SU9PV0xMzEXrlZk8ebLy8vLcW1ZWlndOBAAAAAAAL/Ja8I6MjNSePXs8xnbv3q2WLVuqcePGCgoK0jfffOOulZaWauXKlerVq5e6deumdevWqbS01F3fs2ePioqKKv3styQFBwfL4XB4bAAAAAAAVDdeC979+vVTamqqXn/9dZ05c0bvv/++li1bpqSkJElnv9t7+PDhys7O1qlTpzR27Fj17t1bLVu2VLNmzXT99ddr4sSJys/PV1ZWlkaMGKGpU6d6qz0AAAAAAHzCa8E7NDRUa9eu1aJFixQREaFZs2Zp1apVatSokSRp1KhR6tOnj37961+rWbNmKi4u1ty5c937v/rqqzp+/LgiIiLUpUsXDRgwQMOGDfNWewAAAAAA+ISfZVmWr5vwBpfLJafTqby8PG47/xlaPPKhr1tALXFwVl9ftwAAAAB41aXmUK9+jzcAAAAAAPBE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGHRZwfumm26Sv7+/nn322fPOKSkp0bRp0zzG5s2bp+joaIWGhioxMVE5OTke88eNG6f69esrPDxcDz74oEpLSy+nPQAAAAAAqo3LCt4bNmxQcnLyBeckJyfriy++cL9es2aNnnrqKa1atUrHjh1TfHy8EhMT3fVp06bp22+/1b59+7Rv3z7t3bu3QnAHAAAAAKCmMXKr+datW/X88897jL3wwgt67rnn1LFjR9ntds2YMUPl5eVav369iouLNX/+fL3xxhtq0qSJGjVqpEWLFum1117T6dOnTbQIAAAAAECV8Hrwzs/PV1JSkv72t7+5xyzLUmpqqvr27esxd9CgQVq3bp127dqldu3aKSIiwl0LDw9X165d9a9//cvbLQIAAAAAUGW8HrzHjx+vvn37qk+fPu6x3NxchYWFyWazecyNjY3VgQMHlJmZqdatW1c41rl6ZYqKiuRyuTw2AAAAAACqG68G75UrV2r79u2aPXu2x3hBQYFCQkIqzLfb7SooKLhovTIzZ86U0+l0b1FRUd45CQAAAAAAvMhrwfvIkSMaM2aMlixZUmFl2263q7CwsMI+ubm5CgkJuWi9MpMnT1ZeXp57y8rK8s6JAAAAAADgRQHeOtBf/vIX5eTk6Le//a0kqby8XGVlZYqIiNAPP/ygkydPqqSkRIGBge590tPTFRMTo+joaKWnp1c4Znp6ugYOHFjp+wUHBys4ONhb7QMAAAAAYITXVrzfffddlZSUqLCwUIWFhfr4449122236fDhw/Lz81OnTp20fv16j31SUlLUu3dvXXvttdq7d69OnDjhrh0/flypqam6/vrrvdUiAAAAAABVzsjXiVVm0qRJmjBhgvbt26fCwkLNmDFDdrtdPXv2VFBQkP785z9rxIgRys3N1bFjxzR06FA98MAD573VHAAAAACAmqDKgvett96qCRMmqE+fPmrQoIF27typd999112fPn26rrrqKrVq1Upt27ZVmzZt9Pjjj1dVewAAAAAAGOFnWZbl6ya8weVyyel0Ki8vTw6Hw9ft1BgtHvnQ1y2gljg4q6+vWwAAAAC86lJzaJWteAMAAAAAUBsRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAIArzE033SR/f389++yzHuNbtmxR165d5XA4dN1112n79u3uWnl5uR5//HFFRkaqYcOGGjFihPLz88/7Hs8884yOHTtm7BwAALiSELwBALjCbNiwQcnJyR5jaWlpGjx4sJ588knl5OTooYceUv/+/ZWdnS1Jev7557Vz50599tlnyszMVHR0tMaOHVvp8b/66itNmzbN+HkAAHClIHgDAFALvPzyy5o0aZJ69+4tu92uAQMGKCkpSW+//bYkaePGjRo/fryaNm2qkJAQPfzww3r//fcrHKe4uFj33nuvSktLq/oUAACosQjeAADUAi1btlRCQoLHWFRUlHJyciRJd955p5544gllZGTo1KlTmjx5sho2bFjhOFOmTFGHDh0UGRlZJX0DAHAlCPB1AwAAwLwJEyZUGFu1apWGDRsmSbr//vv1/vvvq0WLFpKksLAwvffeex7zN23apJSUFO3atUvXXHON6ZYBALhiELwBAKiF3njjDR0+fFiJiYmSpIcfflilpaXav3+/GjRooNdff13ff/+9e77L5dJ9992nhQsXyul0+qptAABqJII3AAC1zI4dO/Twww9r48aNCggI0NGjR/Xmm28qLS1NDodDkvTXv/5Vd955p9q3b69rrrlG48aN08CBA9WzZ0/fNg8AQA3EZ7wBAKhFMjMzlZiYqNdff13t2rWTJB04cEBxcXHu0H1Op06d9Omnn2rlypVaunSpXnrpJdlsNtlsNmVkZCgyMlIffPCBL04DAIAaheANAEAtcerUKd1xxx168MEHdccdd7jHW7Zsqf3791d4UvnOnTsVERGhhIQElZSUqLCw0L01b95c2dnZuvPOO6v6NAAAqHEI3gAA1AJlZWUaPHiwevToofHjx3vUGjdurBtvvFH333+/Dh8+LJfLpaefflq7du0iWAMA4AUEbwAAaoGxY8dqzZo1mjt3rgICAtxbr169JEl///vfVadOHbVr104tW7bUli1btH79+gq3nwMAgJ/Pz7Isy9dNeIPL5ZLT6VReXh5/SfgZWjzyoa9bQC1xcFZfX7eAWoLrGqoK1zUAwKXmUFa8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGXVbwvummm+Tv769nn33WY3zLli3q2rWrHA6HrrvuOm3fvt2jPn36dDVp0kQOh0NDhw5Vfn6+u+ZyuTRkyBDVrVtXTZs21ezZsy+nNQAAAAAAqpXLCt4bNmxQcnKyx1haWpoGDx6sJ598Ujk5OXrooYfUv39/ZWdnS5Lmzp2rFStWaPv27crOzpafn59GjBjh3v/+++9XYGCgDh06pG3btiklJUWvvvrqLzg1AAAAAAB8L8BbB3r55Zc1adIk9e7dW5I0YMAApaam6u2339akSZP0wgsvaNmyZWrZsqWks0G8VatW2r9/v2w2mzZs2KCMjAzZbDY5nU4tWrRIt912m0aOHOmtFgEAAAAAqHJeC94tW7ZU3759PcaioqKUlZWlI0eO6PTp0/rNb37jrgUGBqpfv35av369nE6n+vTpI5vN5q63a9dOdevWVVpamtq0aeOtNgEAAAAAqFJee7jahAkTKgTkVatWqVOnTsrMzFTr1q0r7BMbG6sDBw5ctF6ZoqIiuVwujw0AAAAAgOrG2FPN33jjDR0+fFiJiYkqKChQSEhIhTl2u10FBQUXrVdm5syZcjqd7i0qKsrr5wAAAAAAwC9lJHjv2LFDDz/8sP7xj38oICBAdrtdhYWFFebl5uYqJCTkovXKTJ48WXl5ee4tKyvL6+cBAAAAAMAv5bXPeJ+TmZmpxMREvf7662rXrp0kKTo6Wunp6RXmpqenq1OnTnI4HProo48qrcfExFT6PsHBwQoODvZu8wAAAAAAeJlXV7xPnTqlO+64Qw8++KDuuOMO93jjxo0VFBSkb775xj1WWlqqlStXqlevXurWrZvWrVun0tJSd33Pnj0qKiqq9LPfAAAAAADUFF4L3mVlZRo8eLB69Oih8ePHV6hPnDhRw4cPV3Z2tk6dOqWxY8eqd+/eatmypZo1a6brr79eEydOVH5+vrKysjRixAhNnTrVW+0BAAAAAOATXgveY8eO1Zo1azR37lwFBAS4t169ekmSRo0apT59+ujXv/61mjVrpuLiYs2dO9e9/6uvvqrjx48rIiJCXbp00YABAzRs2DBvtQcAAAAAgE/4WZZl+boJb3C5XHI6ncrLy5PD4fB1OzVGi0c+9HULqCUOzurr6xZQS3BdQ1XhugYAuNQcauzrxAAAAAAAAMEbAAAAAACjCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGDQZQXvm266Sf7+/nr22Wc9xrdu3aprr71WdrtdnTt31meffeZRnzdvnqKjoxUaGqrExETl5OS4ayUlJRo3bpzq16+v8PBwPfjggyotLb2c9gAAAAAAqDYuK3hv2LBBycnJHmM5OTlKTExUcnKyXC6XpkyZooSEBB0+fFiStGbNGj311FNatWqVjh07pvj4eCUmJrr3nzZtmr799lvt27dP+/bt0969ezVt2rRfcGoAAAAAAPie1241X7Bgge6++24NGDBAgYGB6t+/v5KSkvTKK69Ikl544QU999xz6tixo+x2u2bMmKHy8nKtX79excXFmj9/vt544w01adJEjRo10qJFi/Taa6/p9OnT3moRAAAAAIAq57XgvXnzZiUkJHiMDRo0SOvWrZNlWUpNTVXfvn0rre/atUvt2rVTRESEuxYeHq6uXbvqX//6l7daBAAAAACgynkteGdmZqp169YeY7GxsTpw4IByc3MVFhYmm81Wab2yfX9cr0xRUZFcLpfHBgAAAABAdeO14F1QUKCQkBCPMbvdroKCgkprP6demZkzZ8rpdLq3qKgo75wIAAAAAABe5LXgbbfbVVhY6DGWm5urkJCQSms/p16ZyZMnKy8vz71lZWV550QAAAAAAPAirwXv6Ohopaene4ylp6crJiZG4eHhOnnypEpKSiqtV7bvj+uVCQ4OlsPh8NgAAAAAAKhuvBa8b7jhBq1Zs8ZjLCUlRb1795afn586deqk9evXV1q/9tprtXfvXp04ccJdO378uFJTU3X99dd7q0UAAAAAAKqc14L3sGHD9Oabb+qjjz5SaWmpVq1apbfeekujR4+WJE2aNEkTJkzQvn37VFhYqBkzZshut6tnz54KCgrSn//8Z40YMUK5ubk6duyYhg4dqgceeOC8t5oDAAAAAFATeC14N2nSRO+8844mT56sunXr6vHHH9eKFSvUuHFjSdKtt96qCRMmqE+fPmrQoIF27typd999173/9OnTddVVV6lVq1Zq27at2rRpo8cff9xb7QEAAAAA4BN+lmVZvm7CG1wul5xOp/Ly8vi898/Q4pEPfd0CaomDs/r6ugXUElzXUFW4rgEALjWHem3FGwAAAAAAVETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAg7wavHNzc3XPPfeoQYMGio6O1nPPPeeuff3117rhhhtkt9vVvn17rV692mPfFStWqG3btrLb7br55puVlpbmzdYAAAAAAPAJrwbvpKQktW7dWllZWdqxY4c2b96sN998U0VFRbr99tv1hz/8QXl5eZo7d66GDx+u3bt3S5J2796tkSNHav78+crLy9PgwYN16623qrCw0JvtAQAAAABQ5bwavDdt2qRHH31UoaGhatKkicaOHav33ntPy5cvV3x8vMaMGaOgoCB1795dycnJeuaZZyRJL7/8sh566CHdeOONCgoK0qhRo9S5c2ctW7bMm+0BAAAAAFDlvBq8+/btq4ceekgul0tZWVl66qmn1KRJE23evFkJCQkecwcNGqR169ZJ0kXrAAAAAADUVF4N3nPmzNG7774rp9Op6Oho/fDDD3rssceUmZmp1q1be8xt2LChCgsLVVRUpEOHDikmJsajHhsbqwMHDpz3vYqKiuRyuTw2AAAAAACqG68F79LSUt1555364x//qNzcXGVkZOjWW2/VkSNHVFBQoJCQkAr72O12FRQUqLy8XP7+/pXWzmfmzJlyOp3uLSoqylunAgAAAACA13gteK9atUp2u12zZ892P9V8xowZ+vOf/6ygoKBKH5R2/PhxhYSEyN/fX5ZledRyc3MrDevnTJ48WXl5ee4tKyvLW6cCAAAAAIDXeC14f/PNN+revbvHWGhoqMLCwiRJ6enpHrXDhw+rQYMGCgoKUrNmzZSZmelRT09Pr3D7+Y8FBwfL4XB4bAAAAAAAVDdeC94xMTHat2+fx1hhYaG+/vpr3XPPPVqzZo1HLSUlRb1795Yk3XDDDResAwAAAABQU3kteN95553auXOn5syZo1OnTunQoUNKSkrSb3/7Ww0cOFCfffaZFi1apJKSEm3btk1PP/20HnzwQUnS2LFj9cQTTyg1NVUlJSVasGCBvvrqK/3hD3/wVnsAAAAAAPiE14K3zWbTqlWr9P7776tJkybq2rWrGjdurEWLFslms+mDDz7QvHnzVK9ePQ0bNkzz5s1T+/btJUkdOnTQSy+9pHvvvVcOh0NLlizR6tWrFRwc7K32AAAAAADwiQBvHqxNmzZau3ZtpbW4uDht2bLlvPv2799f/fv392Y7AAAAAAD4nFe/xxsAAAAAAHgieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEFGg3dGRobefPNNk28BAAAAAEC1ZjR4jx8/Xjk5Oe7XW7du1bXXXiu73a7OnTvrs88+85g/b948RUdHKzQ0VImJiR77AgAAAABQExkL3qtXr9b+/fs1adIkSVJOTo4SExOVnJwsl8ulKVOmKCEhQYcPH5YkrVmzRk899ZRWrVqlY8eOKT4+XomJiabaAwAAAACgShgJ3kVFRZowYYLmzp2rgIAASdKCBQt09913a8CAAQoMDFT//v2VlJSkV155RZL0wgsv6LnnnlPHjh1lt9s1Y8YMlZeXa/369SZaBAAAAACgShgJ3k8//bR69Oihbt26ucc2b96shIQEj3mDBg3SunXrZFmWUlNT1bdv30rrAAAAAADUVF4P3llZWZo5c6bWrl2r+vXr669//avKy8uVmZmp1q1be8yNjY3VgQMHlJubq7CwMNlstkrrlSkqKpLL5fLYAAAAAACobrwevGfMmKE+ffro888/186dO7VlyxbNmTNHBQUFCgkJ8Zhrt9tVUFBQae3H9crMnDlTTqfTvUVFRXn7VAAAAAAA+MUCvH3AlStXat++fapfv74k6fXXX9fgwYNlt9tVWFjoMTc3N1chISGV1n5cr8zkyZPdD26TJJfLRfgGAAAAAFQ7Xl3xPnr0qEJDQ92hW5Lat2+v7OxsRUdHKz093WN+enq6YmJiFB4erpMnT6qkpKTSemWCg4PlcDg8NgAAAAAAqhuvBu/w8HCdOHFCJ06ccI/t3btX0dHRuuGGG7RmzRqP+SkpKerdu7f8/PzUqVOnCk8wP1cHAAAAAKCm8mrw9vf313333af77rtPR44cUXp6uoYPH67x48dr2LBhevPNN/XRRx+ptLRUq1at0ltvvaXRo0dLkiZNmqQJEyZo3759Kiws1IwZM2S329WzZ09vtggAAAAAQJXy+me8Z82apYcffljx8fEKDQ3VuHHjNGLECEnSO++8ozFjxigxMVHx8fFasWKFGjduLEm69dZblZGRoT59+ig3N1e33HKL3n33XW+3BwAAAABAlfKzLMvydRPe4HK55HQ6lZeXx+e9f4YWj3zo6xZQSxyc1dfXLaCW4LqGqsJ1DQBwqTnU618nBgAAAAAA/ovgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwyGjwfuaZZ3Ts2DFJ0tdff60bbrhBdrtd7du31+rVqz3mrlixQm3btpXdbtfNN9+stLQ0k60BAAAAAFAljAXvr776StOmTZMkFRUV6fbbb9cf/vAH5eXlae7cuRo+fLh2794tSdq9e7dGjhyp+fPnKy8vT4MHD9att96qwsJCU+0BAAAAAFAljATv4uJi3XvvvSotLZUkLV++XPHx8RozZoyCgoLUvXt3JScn65lnnpEkvfzyy3rooYd04403KigoSKNGjVLnzp21bNkyE+0BAAAAAFBljATvKVOmqEOHDoqMjJQkbd68WQkJCR5zBg0apHXr1l1SHQAAAACAmsrrwXvTpk1KSUnRnDlz3GOZmZlq3bq1x7yGDRuqsLBQRUVFOnTokGJiYjzqsbGxOnDgwHnfp6ioSC6Xy2MDAAAAAKC68Wrwdrlcuu+++7Rw4UI5nU73eEFBgUJCQirMt9vtKigoUHl5ufz9/Sutnc/MmTPldDrdW1RUlPdOBAAAAAAAL/Fq8B43bpwGDhyonj17eozb7fZKH5R2/PhxhYSEyN/fX5ZledRyc3MrDevnTJ48WXl5ee4tKyvLK+cAAAAAAIA3BXjrQCtXrtTSpUtVp04dvfTSS5LO3g4eGRmpq666Sunp6erRo4d7/uHDh9WgQQMFBQWpWbNmyszMVPPmzd319PT0Cref/1hwcLCCg4O91T4AAAAAAEZ4bcU7ISFBJSUlKiwsdG/NmzdXdna2nnzySa1Zs8ZjfkpKinr37i1JuuGGGy5YBwAAAACgpjL2Pd4/NmDAAH322WdatGiRSkpKtG3bNj399NN68MEHJUljx47VE088odTUVJWUlGjBggX66quv9Ic//KEq2gMAAAAAwJgqCd42m00ffPCB5s2bp3r16mnYsGGaN2+e2rdvL0nq0KGDXnrpJd17771yOBxasmSJVq9eza3kAAAAAIAaz2uf8a7MwYMH3f87Li5OW7ZsOe/c/v37q3///ibbAQAAAACgylXJijcAAAAAALUVwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAzyavA+ceKEkpKS1KhRI7Vo0UKzZs1SeXm5JGnr1q269tprZbfb1blzZ3322Wce+86bN0/R0dEKDQ1VYmKicnJyvNkaAAAAAAA+4dXgPWjQIDVr1kz79+/XJ598ohUrVujll19WTk6OEhMTlZycLJfLpSlTpighIUGHDx+WJK1Zs0ZPPfWUVq1apWPHjik+Pl6JiYnebA0AAAAAAJ/wWvD+4osvdOTIET355JNyOBxq06aNFi5cqNdee00LFizQ3XffrQEDBigwMFD9+/dXUlKSXnnlFUnSCy+8oOeee04dO3aU3W7XjBkzVF5ervXr13urPQAAAAAAfMJrwbusrEyTJk2Sn5+feywqKko5OTnavHmzEhISPOYPGjRI69atk2VZSk1NVd++fSutAwAAAABQkwV460CdOnVSp06dPMZWrVqlTp06KSMjQ61bt/aoxcbG6sCBA8rNzVVYWJhsNluF+rJly877fkVFRSoqKnK/drlcXjgLAAAAAAC8y9hTzQ8fPqy//vWvSk5OVkFBgUJCQjzqdrtdBQUFldZ+XD+fmTNnyul0ureoqCivnwMAAAAAAL+UkeBdVFSkgQMHavTo0eratavsdrsKCws95uTm5iokJKTS2o/r5zN58mTl5eW5t6ysLK+fBwAAAAAAv5TXbjX/sWHDhikqKkqPPvqoJCk6Olrp6emKjo52z0lPT1dMTIzCw8N18uRJlZSUKDAwsEL9fIKDgxUcHGyifQAAAAAAvMbrK96PP/64Dhw4oDfeeMP9oLUbbrhBa9as8ZiXkpKi3r17y8/PT506darwBPNzdQAAAAAAajKvrngvXbpUixcv1rZt2zweljZs2DD96le/Uo8ePdSnTx+tWbNGb731lnbu3ClJmjRpkiZMmKD33ntPLVq00DPPPCO73a6ePXt6sz0AAAAAAKqc14L35s2bNXToUJWUlKhp06Yetf379+udd97RmDFjlJiYqPj4eK1YsUKNGzeWJN16663KyMhQnz59lJubq1tuuUXvvvuut1oDAAAAAMBnvBa8u3fv7vH1Xj/VvHlz7dq167z1kSNHauTIkd5qBwAAAACAasHY14kBAAAAAACCNwAAAAAARhG8AQAAAAAwiOANAAAAAIBBBG8AAAAAAAwieAMAAAAAYBDBGwAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQQRvAAAAAAAMIngDAAAAAGAQwRsAAAAAAIMI3gAAAAAAGETwBgAAAADAIII3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAwBXto48+0meffebrNlCLEbwBAAAAXBGeeeYZHTt2zGMsPz9fo0aNUnl5uY+6AgjeAAAAAK4AX331laZNm1ZhfPr06brtttt03XXX+aAr4KwAXzcAAAAAAL9EcXGx7r33XpWWlnqM79u3T//4xz+0e/duH3UGnEXwBgAAAFCjTZkyRR06dFBeXp7H+AMPPKCZM2cqLCzMN40B/z9uNQcAAABQY23atEkpKSmaM2eOx3hKSorWr1+vRx99VJGRkVq8eLGPOgQI3gAAAABqKJfLpfvuu08LFy6U0+l0j1uWpSlTpuh//ud/tHfvXi1btkwPPvigvvzySx92i9qM4A0AAACgRho3bpwGDhyonj17eozv2rVLTqdT06ZNU926ddWjRw9NnTpVr776qm8aRa1H8AYAAABQ46xcuVJLly7VSy+9JJvNJpvNpoyMDEVGRmrPnj2Kj4/3mN+xY0dlZGT4qFvUdgRvAAAAADVOQkKCSkpKVFhY6N6aN2+u7OxstW7dWnv27PGYv3v3brVs2dJH3aK2I3gDAAAAuKJ07dpV5eXlmjFjhvLz87V582bNnDlTo0eP9nVrqKX4OjEAAAAAVxR/f3+9//77GjlypJo1a6aWLVvqjTfeUFxcnK9bQy1F8AYAAACqsRaPfOjrFmqO389Rp2dT//u6/SjVbz9KJyUN/7RI+pSf5YUcnNXX1y1csbjVHAAAAAAAgwjeAAAAAAAYRPAGAAAAAMAggjcAAAAAAAYRvAEAAAAAMIjgDQAAAACAQdUqeLtcLg0ZMkR169ZV06ZNNXv2bF+3BAAAAADAL1Ktvsf7/vvvl81m06FDh3Ty5EkNGjRIYWFhGjlypK9bAwAAAADgslSb4H3o0CFt2LBBGRkZstlscjqdWrRokW677TaCNwAAAACgxqo2t5pv3bpVffr0kc1mc4+1a9dOdevWVVpamg87AwAAAADg8lWbFe/MzEy1bt26wnhsbKwOHDigNm3aeIwXFRWpqKjI/TovL0/S2c+J49KVF53xdQuoJfhvE1WF6xqqCtc1VBWua6gqXNd+vnM/M8uyLjiv2gTvgoIChYSEVBi32+0qKCioMD5z5kz9z//8T4XxqKgoI/0B+GWc/8/XHQCAd3FdA3Cl4bp2+U6dOiWn03neerUJ3na7XWfOVPzXvNzc3EoD+eTJkzVp0iT36/Lych0/flzh4eHy8/Mz2itqN5fLpaioKGVlZcnhcPi6HQD4xbiuAbjScF1DVbEsS6dOnVLTpk0vOK/aBO/o6Gh99NFHFcbT09MVExNTYTw4OFjBwcEeY2FhYabaAypwOBxcyAFcUbiuAbjScF1DVbjQSvc51ebhat26ddO6detUWlrqHtuzZ4+Kiooq/ew3AAAAAAA1QbUJ3s2aNdP111+viRMnKj8/X1lZWRoxYoSmTp3q69YAAAAAALhs1SZ4S9Krr76q48ePKyIiQl26dNGAAQM0bNgwX7cFeAgODtZjjz1W4aMOAFBTcV0DcKXhuobqxs+62HPPAQAAAADAZatWK94AAAAAAFxpCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAAAAAIBBBG/gZzp9+rQ6duyo0tJS99jGjRs1ZcoUjzEAqCny8/PlcDg8rmGrV6/WkCFDVFxc7MPOAOD88vLyNH78+PPWQ0NDdfToUffr06dPV0VbQKUI3sDPFBwcrL1798qyLL355pvu8VmzZqmwsNCHnQHA5bHb7Tpz5ozKyso0Y8YMSVK9evX01ltvEbwBVFt+fn5avny5JGn+/Pl68cUX9b//+7+aP3++pLPXttDQUElSTk6O2rZtq4yMDJ/1i9rNz7Isy9dNANXR6dOn9bvf/U7BwcGSJMuy5HQ6tWLFCtWtW1fHjx9XRESEjh8/rl27duk3v/mNXC6X+wIPANVNfn6+YmNjPa5r4eHh+ve//6169eq5r2u5ubn68ssv9etf/5rrGoBqq6ioSPHx8UpLS9PVV1+t7t27S5I2bNig7777Ts2bN3cH7Tlz5uj111/Xzp07fdkyajFWvIHzCA4OVlZWloYNG6bvvvtOw4cP17fffitJstlsCgoKUkBAgPu1JAUFBfmsXwC4GLvdLpvNpsWLF8vPz09LlizRmTNnJJ295gUGBrqva+euZ+dCOgBUNwEBAR7XrPnz52v+/PmqU6eOe6xfv37KycnRu+++q7/97W++bBe1HMEbOI+AgACFhYVpyJAh7l/9/f3dNUkKDAyUJJWUlCgwMND9GgCqozp16ig0NFTdunVz//rT69q5wF1cXCybzeYeB4Dqpk6dOsrJydHo0aN1+PBhjR49WqNHj/a4rt18883q3r27du/erYEDB/q4Y9Rm/L8p8DOcu5AXFRVp+vTpys/P1/Tp03Xo0CFFRET4uDsA+PnOXdcKCgo0dOhQnThxQkOHDtXRo0d11VVX+bg7ALgwu92ubt26afXq1erWrZssy9KGDRsknf0M+IQJE3Tq1CmtXr2aO3jgU6x4Az/DuUcilJeXKy0tTf369VNaWpp27dqla665xsfdAcDPd+665u/vr2bNmmnixIlq1qyZiouL1alTJx93BwAX5nQ6NWTIENWvX19DhgzRPffcI0maMGGCXC6XJOn777/XV199pS+++MKXraKWY8Ub+BnO/QXVbrdr8eLF7vHbb7/dfaEHgJrk3HUtKCjI/URzy7LUrVs3TZo0yZetAcBFHTx4UF26dFFaWpq6dOniHm/cuLFOnDihjz76SP/85z81YsQIpaSk6Fe/+pUPu0Vtxoo3cB5lZWUqLi7Wt99+6/713HfclpaWavfu3fr666/dXyN21113+bhjALiwsrIy5efn6+OPP3b/eu66VlZWpn/9619au3atxowZo5YtW+qWW27xcccAcGERERFavHixoqOjtWTJEi1atEiWZenRRx9V06ZNNXXqVNlsNiUkJGjr1q2+bhe1GCvewHkUFhbq22+/Vbt27WRZlq6++mpFRkZKOvsZ7y+++EIjR45U3bp1tX37dh93CwAXV1BQoMLCQo0cOVKSNHLkSDVo0EDS2WveuYcTlZWVac2aNb5sFQAuqry8XAEBAYqNjVWdOnXk5+cnPz8/lZeXSzq7ULJ582Z98sknatq0qb788ksfd4zajO/xBi7g3NPKzykuLlZAQIBsNpuKi4uVm5urF154QX//+981depUTZw40YfdAsDlKSsrk81mU0lJicrKyrRw4UI98sgjGjJkiJ5++mkeSASgWiosLFS7du2Unp6uHj16KCcnRyUlJWrSpIm2bdumyMhIHTx4UAEBATp27JgaN26s3Nxc1a9f39etoxYieAM/05kzZ1S3bl2VlJS4vydy27ZtGjp0qLZs2aLw8HAfdwgAP09+fr4cDof7Hxclaf/+/Ro2bJg+/PBDhYaG+rhDAKjo+PHjatWqlU6cOFFp3el0KisrSw6HQ6dOndKiRYt0//338/Wv8AmCN3ABZWVlOnTokKKiouTn5yfp7G1NX3/9teLi4txj0tlAHhIS4qtWAeAXOX36dIWAbVmWx3UOAGqSjz76SL179yZoo1ogeAMXkJWVpRYtWujw4cNq1KiRR2348OHq0KGDxo8f76PuAAAAANQEPNUcuIDQ0FBZllVhJXvUqFFavHix6tWr56POAAAAIElHjx5VdHT0eW85l84upvzud7+rwq4ATzzVHLiA4OBg+fn5KSgoyD02btw4paSk6NNPP1X37t192B0AAEDtdurUKdntdmVnZ8tutysrK0t2u12WZamgoEB2u13z58/Xfffdp3//+9++bhe1GCvewAWc+0zQuYcNLV++XAsXLtTq1asJ3QAAAD705ptv6m9/+5tsNpv8/Pxks9nUtm1bNWnSRBEREWrZsqVWrlypmTNnyuFwyGaz+bpl1GIEb+AC6tSpI8uytHTpUklSQkKCPv30U3Xp0sXHnQEAANRu3377rfu7vP39z8aaFi1aqKysTF26dNGCBQsUGhqq8PBwBQcHuxdSAF/gTx9wCcaPH6/nn39e8fHxkqQ5c+Z41EtLS3Xy5EmtXr3aF+0BAADUOh07dtSHH34oSe6PBQYHB7vr5z4uWK9ePQUEBBC84VOseAMX4efnp2+++UZdunTR0qVLtX37dpWUlHhsxcXFKi4u9nWrAAAAtUZMTIzS09O1adMmSdKmTZt05swZbdq0SS6XS/v27VNaWpoKCwu1efNm96o44At8nRhwAaWlpQoODlZZWZkkacmSJRozZoyWL1+uXr16+bg7AACA2iszM1NxcXFq166ddu3apWuvvVZ79+5VXFyc9u3bp0aNGikgIEDff/+92rVrp7y8PH377be+bhu1FP/sA1xAaWmpJLmD9z333KPFixcrMTFRqampvmwNAACgVmvQoIGio6O1Y8cOBQcHa8eOHWrTpo127Nih+Ph4Pf7443ruuecUExOjHTt2uP8+B/gCwRu4gJKSEkn/DeCS1K9fPz3wwAO66667Lvh9kQAAADDHbrfr5MmTkv67SPLTcF1eXq4zZ87IsiyVl5dXdYuAG8EbuIDCwkJJUlFRkcf4jBkzZLfblZSU5Iu2AAAAar06deqooKBAlmW5F0uOHz+u5ORkZWdna/ny5SooKNCJEydUVFTksZACVDWCN3ABxcXFiouLc1/Mz6lTp46Sk5PlcDj411MAAAAfKCkpUXl5uQoLC2VZlsrKynTffffJz89PQ4cOVWxsrK666ioFBAQoPz+/wkIKUJV4uBpwmSzLUmlpqQIDA33dCgAAQK1TXFysf/7zn/rVr36lxo0b6+TJk3I4HJXOzcjIUFxcnE6fPl3FXQJnseINXCY/Pz9CNwAAgI8EBQXp5ptv1pEjRzR37lyP7/D+qYYNG+q9996rwu4AT6x4AwAAAKiRsrKy1KJFCx0+fFiNGjXyqA0fPlwdOnTQ+PHjfdQd8F+seAMAAACokUJDQ2VZlkJCQjzGR40apcWLF6tevXo+6gzwFODrBgAAAADgcgQHB8vPz09BQUHusXHjxiklJUWffvqpunfv7sPugP8ieAMAAACokc49bycg4GysWb58uRYuXKh169apS5cuvmwN8MCt5gAAAABqpDp16siyLC1dulSSlJCQoE8//ZTQjWqHh6sBAAAAqJHKysoUGBio+vXrq3nz5oqPj690XmlpqU6ePKnVq1dXcYfAWax4AwAAAKix/Pz89M0336hLly5aunSptm/frpKSEo+tuLhYxcXFvm4VtRgr3gAAAABqpNLSUgUHB6usrEyStGTJEo0ZM0bLly9Xr169fNwd8F88XA0AAABAjVRaWirp7C3nderU0T333COHw6HExER98skn6tq1q487BM7iVnMAAAAANVJJSYmk/wZwSerXr58eeOAB3XXXXTpx4oSvWgM8cKs5AAAAgBrp6NGjioiI0IkTJ+RwONzjZWVliouLU2xsrN5//30fdgicxYo3AAAAgBqpuLhYcXFx7pXvc+rUqaPk5GQ5HA6Vl5f7qDvgv1jxBgAAAHDFsSxLpaWlCgwM9HUrAMEbAAAAAACTuNUcAAAAAACDCN4AAAAAABhE8AYAAAAAwCCCNwAAAAAABhG8AQAAAAAwiOANAPC6zz//XI0aNdL3339/SfNbtGihY8eOGe3p8ccf17PPPuuVY61evVo33nijJKlz58566aWXfNLH+Rw8eFDx8fG/6BhbtmxR165d5XA4dN1112n79u2XvO8nn3wif39/BQQEuLecnJxK5y5atMhjXkBAgPz9/ZWQkCDJ7M/Lm8fu2bOn/v3vf19wzrFjx9SoUSP5+flddC4A4MpC8AYAeF29evXUtm1b2e12X7dixDvvvKO77rpLktSmTRs1btzYxx15V1pamgYPHqwnn3xSOTk5euihh9S/f39lZ2df0v7/+c9/9Nhjj6m0tNS9NWnSpNK5f/rTnzzmFRcXq127dpo6dao3T6laaNiwoY4ePer+RxsAQO1B8AYAeF3btm21detW1a9f39eteF1JSYk++OADDRw4UJK0bNky3X333T7uyrtefvllTZo0Sb1795bdbteAAQOUlJSkt99++5L2/89//qOrr776st773XffVXR0tDp37nxZ+wMAUB0RvAEAXnfs2DG1aNHCfcvz3r171bNnT4WEhKhTp07auXOnpLMBLSAgQBkZGYqIiND48ePdx1iyZIni4uIUHBysVq1a6bnnnpNlWZKkjRs3qm/fvrrnnnsUERGh06dPq2fPntq6dasmTpyo8PBwNWnSRM8//3yl/d13331asmSJ/vKXv8jhcCgmJkYffvihiouLNW7cONWvX1+tWrXSRx99VGHfTz/9VHFxcbrqqqskSXfccYc2btwoSRft4brrrtP06dP18MMPKywszD2elpamO++8U3Xr1lX9+vU1ZMgQ/fDDD+56ixYt9Nprr8npdOrtt9/WG2+8oQceeEArVqxQXFyc6tatq/79+ys3N7dCvxs3btQdd9yhd955R61atZLD4dDYsWNVXl6u9957T1dffbXCwsI0fvx4lZWVSZJatmzpvtX7nKioqPPeLv5Te/fuVWxs7CXN/THLsvTkk09q2rRpFWoLFizQ1VdfLZvNpmuuuUbvvffeJR1z7dq16tatm0JCQtSwYUP98Y9/1MGDBz3mzJs3TzExMXI4HBo6dKgKCws96i+99JJat24tu92uzp07a926dRo0aJA2btyo06dPKyAgQP/85z913XXXVfi5Xapf8mcSAFD9EbwBAEbl5uYqKSlJs2fPVm5urkaNGqWEhASVlJSoffv2Ki0tVfPmzXX48GG9+OKLks4Goblz5+qtt95Sfn6+Vq5cqU8++UQPPfSQ+7gbNmxQu3btlJGRodDQUEnSAw88oMjISGVnZ+vTTz/VnDlzzhtUkpOTFRcXpyNHjmj+/Pn605/+pJEjRyo2NlY//PCDFi5cqKSkJJ0+fdpjv3feeUeDBg067/leqIft27crOTlZs2fP1smTJyVJ2dnZuuWWW3TPPffoyJEj+u6779SxY0f17NlTLpfLfdw333xTBw4ccL/3xo0b9corr+jjjz9WVlaWGjdurNGjR1fa05dffqlFixZp06ZNSktL0+eff67Ro0drwYIFWr9+vdLS0rRr1y4tWbJEkjRhwgS1adPG4xirVq1Sp06dznveP/af//xHAwYMUHh4uAYNGqQjR45c0n4ffPCBwsPDdf3113uMv/baa1q7dq0++OADHT9+XDNnztS4ceP01ltvXfB4//d//6eRI0fqoYce0pEjR5SWlqZu3bqpR48eOnHihKSznzHfuHGjUlNTlZaWptzcXD322GPuY0ybNk0LFizQ0qVLdfz4cf3v//6vHnnkEe3atUuSFBoaqtLSUt14443avn27Vq5ceUnnWpnL/TMJAKgBLAAAvOzo0aNW8+bNrfT0dEuStX37do96586drc8++8z9unnz5tbRo0cty7KswsJCKzIy0v36nKKiIisyMtI6cuSItWHDBissLMwqLi5212+88UZr1KhRHvvMmTPHGj16tGVZlvXYY49ZzzzzjGVZlpWUlGTdfffdHnN/97vfWb///e89xm6//XZr06ZN7tclJSVWw4YNrezsbPdY3759rQ0bNlxSDz/tw7Isa/To0dYrr7xi/dTEiROt559/3v3zefvtt921hQsXWuHh4VZ+fr57LC8vzwoLC7PKy8ut9PR0q3379pZlWdaGDRssm81mnThxwj132bJllt1ut44fP+4ee/vtt62hQ4dW6OPc+11zzTVWSUlJpfUfKygosJYvX26dOHHCOnnypDVt2jSrW7duF93Pss7+uTj3szznscceszp16mSVlZV5jKemplrNmjWrMH5OcXGx1axZM2v37t0Vaj/88IP72HFxcVZ5ebm7tm/fPisuLs6yLMs6dOiQ1ahRI+vw4cMe+2dlZVn16tXz6PXGG2+0duzYcUnnWdncy/0zCQCoGVjxBgAY1bRpU3Xt2tVjrHXr1jp8+HCl83fv3q1Dhw4pMjJSNpvNvTkcDuXk5OjLL7+UJMXFxSkwMNBj3wEDBlzy+/Ts2dPjdaNGjdS9e3ePsfDwcI/bt9etW6fY2Fg1a9bsvOf7c3qQpH/+85+aMGGCx7nabDbNmTNHX3zxhXvetdde67HfLbfc4l7plySHwyG73a78/PwK73HNNdd43NreqFEjxcfHe3wG/6fnes6OHTv08MMP6x//+IcCAgLOex7n2Gw2JSYmKiwsTE6nU9OnT9eZM2e0e/fuC+63du1aBQcHV/h9kaSEhAT5+3v+laVLly6qW7eu0tLSKj3e7t271bRp00qf7h4REeH+3/3795efn5/7dUxMjPv361//+pduvPHGCg+Gi4yMVLdu3S54Ppfjcv5MAgBqBoI3AMAop9NZYSwoKEhFRUXn3adLly4qLCyssBUXF6t3796SzgbNi73Xhd7npw9+CwgIUIMGDTzG/P39VVpa6n7946eZn8/P6eGcL7/8ssK5FhUVadGiRe45Pz3fn/NzvZxzlaTMzEwlJibq9ddfV7t27S54DhcSExOj7OxsPfzwwx5fG/af//zHPed8n+2WVKGvn7r77rs9jnv69GmVlZVddD+p4s8xMDDQ/TP08/NzP1fg53jllVc8+lm9evUl7Xe5v08AgOqP4A0AMOqnK5UXEx8fr4yMDGVmZnqM5+fn6y9/+YvKy8slSXXq1PlF71XZ/hda0S0tLdXKlSvdTzM/n597vjfccIM++OCDCuNPP/20e3VfqtivyXOVpFOnTumOO+7Qgw8+qDvuuOOS3qe4uFh9+vRRQUGBe6yoqEg7duxQ27ZtNXv2bI+vDmvfvr2ks6v+RUVF+t3vflfpcVNSUlRSUuIxtn37dp0+fVpt2rTR//3f/3kcNzQ0VB06dFBWVpY+//zzCsf78YPrLvRz7NatmzZt2lThjoVDhw5p69at591v9OjRHv3cfvvt5537Y5fz+wQAqBkI3gAAn/P393cHK5vNpuTkZPXv3187duxQcXGxvvzyS91+++1q2LDhzw623rJ+/Xq1adNGkZGRv+g4Pz5XSZoyZYpefvllvfbaa3K5XDp27Jgee+wxLVy4UK1bt/6lbV+WsrIyDR48WD169PB40vzFBAUFKSwsTGPGjNGJEyf0/fffKykpSZ07d1arVq3Ou9+MGTMu+L3dQUFBGjBggL755hudOXNGq1at0qBBg/T888+f98+DzWbTzJkzlZCQoPfee0+nTp3SiRMn9OKLL+r66693P9zuQiIiIjR69GjddtttSk1NVWFhobZt26YBAwZ43K4uVfx9BQDgxwjeAACfu+mmm9S6dWtt27ZNkvSXv/xF48ePV1JSkurVq6eBAwdq4MCBmjFjhs96TElJueht5pfit7/9rZ566il3oI2KitLatWu1YsUKNW3aVG3bttX+/fu1ceNGj89wV6WxY8dqzZo1mjt3rsct07169brovvPnz1dZWZlatWql9u3bKyQkRAsWLDjv/FOnTik8PFx33nnneef88Y9/1ODBg9WvXz/Vr19f06ZN09///veL/n4MHz5cL774op544gk1atRIsbGx2rlzpzZv3uzxmfcLefzxxzV8+HDdc889CgsL08SJE/X//t//U8eOHT3m9ezZU7169brk7zoHANQuftblfHgJAIBapKysTFdddZU+//xzRUVF+bodAABQw7DiDQDARRw7dkxTp04ldEvq1auXxyr4j7cffyYdAAD8FyveAAAAAAAYxIo3AAAAAAAGEbwBAAAAADCI4A0AAAAAgEEEbwAAAAAADCJ4AwAAAABgEMEbAAAAAACDCN4AAAAAABhE8AYAAAAAwKD/DxqG3xVeGeguAAAAAElFTkSuQmCC","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-562 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-562\n","不重要     1828\n","是        875\n","不是       257\n","回答正确      28\n","问法错误      12\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-1124 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-1124\n","是       1069\n","不是       966\n","不重要      946\n","回答正确      10\n","问法错误       9\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-1686 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-1686\n","不是      1581\n","是        999\n","不重要      383\n","回答正确      24\n","问法错误      13\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA94AAAI3CAYAAABtUYPVAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAABinElEQVR4nO3dd3gUZf/+/TOFZDcJSehICB0iRUClSlF6ryLeihqqCIgUFUVpgoIN0VtQFJUiIF8EBEWK3gjSOyiKICUkAUmEJKTvps3zhw/7Y00o4k42gffrOOYwe13X7H4mO4s5d66Z8TAMwxAAAAAAADCFp7sLAAAAAADgVkbwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARN7uLsBVcnJy9Mcff6ho0aLy8PBwdzkAAAAAgFucYRhKTk5WuXLl5Ol59ePat0zw/uOPPxQaGuruMgAAAAAAt5no6GiVL1/+qv23TPAuWrSopL82ODAw0M3VAAAAAABudUlJSQoNDXXk0au5ZYL35enlgYGBBG8AAAAAQL653unOXFwNAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATmRa8ly5dqhMnTpj19DBBq1at5OnpqbfffjtXX0hIiLy9vR3Lm2++6ej74IMPVKVKFQUHB+uhhx5SbGys07rh4eHy8vLS008/bfo2AAAAAEBBc1PB+1oBTZLOnTunMWPGqEiRIk7tU6dOVZkyZRQYGKiBAwcqJSXF0ZeUlKR+/fopICBA5cqV0xtvvHEzpeFf2Lx5syZNmpSr/dKlS/L19VVWVpZjGTdunCRpxYoVWrRokb777jvFxsaqU6dOeuSRR5zWX7hwoT799NN82QYAAAAAKGhuKnhfLaBdNmbMGI0ZM0aVKlVytM2dO1erV6/W7t27dfbsWXl4eGjIkCGO/ieffFJFihTRuXPntGvXLq1YsUIfffTRzZQHF/v1118VFhaWZ9+WLVs0ZMgQVatWTb6+vho4cKBOnDihS5cu5W+RAAAAAFBAebv6CTdt2qSjR49qyZIlTu2zZs3S0qVLVblyZUl/BfGqVavq1KlTslgs2rx5syIjI2WxWBQUFKRFixapU6dOGjp0qKtLxD909OjRqwbvLl266MUXX1STJk1UpUoVffjhh0pKSpLVas3nKgEAAACgYHLpOd6ZmZl65pln9OGHHzpNM//zzz+Vmpqqe++919FWpEgRde/eXT/88IN27Nihdu3ayWKxOPpr1qypgIAAzhMvAH799VctW7ZMxYsXV/369bVx40ZHX6dOndSsWTPVqVNHfn5+evnll/XRRx/J19fXjRUDAAAAQMHh0uD93nvv6dSpU3rooYdUvXp1fffdd5KkqKgoVatWLdf4sLAwnT59+rr9ebHb7UpKSnJaYI4uXbpo586diomJ0cyZMzVw4EAdPXpU0l8XVtu7d69+/vlnJScna86cObkurgYAAAAAtzOXBe/U1FS9/vrrmjNnjk6dOqW33npL/fr10/nz55Weni4/P79c61itVqWnp1+3Py8zZsxQUFCQYwkNDXXVpuBv2rVrpypVqsjHx0dt2rTRCy+8oE8//VTZ2dmaMmWKVq5cqbvuuksBAQEaOHCgjh8/rrVr17q7bAAAAAAoEFwWvL/77ju1bt1agwYNkr+/v3r27Knw8HB9/vnnslqtstlsudaJi4uTn5/fdfvzMn78eCUmJjqW6OhoV20KrqNKlSo6e/asLl68KH9/f1WsWNGpv3Hjxk7T0QEAAADgduay4H3y5EnVqVPHqa1u3bqKjIxUhQoVFBERkWudiIgIValS5br9efH19VVgYKDTAtebNm2avv76a6e27du3q0aNGipdurRSUlKUmJjo1H/w4EGVLVs2P8sEAAAAgALLZcG7fPny+uWXX5zajhw5osqVK6t06dLy8fHR8ePHHX1ZWVlas2aN2rRpo2bNmmnTpk3Kyspy9P/yyy+y2+15nvuN/HPPPfdo9OjROnz4sNLS0rRgwQJ9+umnGjZsmDw8PPTUU0/p0UcfVUREhFJTU7VgwQItXbpUjz/+uLtLBwAAAIACwWXBu3v37tqzZ48+/fRTpaWl6euvv9bSpUsVHh4u6a97ew8ePFhnz55VcnKyRo4cqbZt26py5coKCQnRfffdpzFjxiglJUXR0dEaMmSIJkyY4KrycJO6dOmi8ePH68EHH1Tx4sX10Ucfac2aNSpXrpwkafLkyapTp46aNGmiO+64Q4sWLdLGjRtVoUIFN1cOAAAAAAWDh2EYxs2sOGXKFAUEBOi5555ztB07dkxDhw7VoUOHVKdOHc2ZM0d33323o3/q1KmaPXu2bDabHnroIf33v/+Vv7+/JCkxMVHDhw/XmjVrVLRoUY0dO1bPP//8DdeTlJSkoKAgJSYmMu0cAAAAAGC6G82hNx28C5rCHLwrvfitu0u47Zx5vYu7SwAAAABQyN1oDnXpfbwBAAAAAIAzgjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGCimwrerVq1kqenp95+++2rjsnMzNTEiROd2j7++GNVqFBB/v7+6tWrl2JjY53GP/PMMypWrJhKlCih559/XllZWTdTHgAAAAAABcZNBe/Nmzdr0qRJ1xwzadIkHTp0yPF4w4YNmj59utauXauLFy+qTp066tWrl6N/4sSJ+v3333Xs2DEdO3ZMR48ezRXcAQAAAAAobEyZar5jxw698847Tm2zZs3SzJkzVbduXVmtVk2bNk05OTn64YcflJGRoXnz5mnBggUqU6aMSpUqpUWLFumTTz5RamqqGSUCAAAAAJAvXB68U1JSFB4erueee87RZhiG9uzZoy5dujiN7dOnjzZt2qTDhw+rZs2aKlu2rKOvRIkSaty4sXbu3OnqEgEAAAAAyDcuD96jRo1Sly5d1K5dO0dbXFycgoODZbFYnMaGhYXp9OnTioqKUrVq1XI91+V+AAAAAAAKK29XPtmaNWu0e/duHThwQLt373a0p6eny8/PL9d4q9Wq9PT06/bnxW63y263Ox4nJSW5YAsAAAAAAHAtlx3x/vPPPzVixAgtXrw415Ftq9Uqm82Wa524uDj5+fldtz8vM2bMUFBQkGMJDQ11zYYAAAAAAOBCLjviPWzYMMXGxqpp06aSpJycHGVnZ6ts2bI6f/68Ll26pMzMTBUpUsSxTkREhKpUqaIKFSooIiIi13NGRETowQcfzPP1xo8fr7FjxzoeJyUlEb4BAAAAAAWOy454r1y5UpmZmbLZbLLZbPruu+/UqVMnxcTEyMPDQw0aNNAPP/zgtM6KFSvUtm1b1a9fX0ePHlVCQoKjLz4+Xnv27NF9992X5+v5+voqMDDQaQEAAAAAoKAx5XZieRk7dqxGjx6tY8eOyWazadq0abJarXrggQfk4+OjAQMGaMiQIYqLi9PFixc1cOBAPf3001edag4AAAAAQGGQb8G7Y8eOGj16tNq1a6fixYvr4MGDWrlypaN/6tSpuuOOO1S1alXVqFFD1atX15QpU/KrPAAAAAAATOFhGIbh7iJcISkpSUFBQUpMTCx0084rvfitu0u47Zx5vcv1BwEAAADANdxoDs23I94AAAAAANyOCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJjopoJ3q1at5Onpqbffftupffv27WrcuLECAwPVpEkT7d6926l/6tSpKlOmjAIDAzVw4EClpKQ4+pKSktSvXz8FBASoXLlyeuONN26mNAAAAAAACpSbCt6bN2/WpEmTnNpOnDihvn376rXXXlNsbKzGjRunnj176uzZs5KkuXPnavXq1dq9e7fOnj0rDw8PDRkyxLH+k08+qSJFiujcuXPatWuXVqxYoY8++uhfbBoAAAAAAO7n7aonmj17tsaOHau2bdtKknr37q09e/Zo+fLlGjt2rGbNmqWlS5eqcuXKkv4K4lWrVtWpU6dksVi0efNmRUZGymKxKCgoSIsWLVKnTp00dOhQV5UIAAAAAEC+c1nwrly5srp06eLUFhoaqujoaP35559KTU3Vvffe6+grUqSIunfvrh9++EFBQUFq166dLBaLo79mzZoKCAjQiRMnVL16dVeVCQAAAABAvnLZxdVGjx6dKyCvXbtWDRo0UFRUlKpVq5ZrnbCwMJ0+ffq6/QAAAAAAFFamXdV8wYIFiomJUa9evZSeni4/P79cY6xWq9LT06/bnxe73a6kpCSnBQAAAACAgsaU4L1v3z698MIL+uKLL+Tt7S2r1SqbzZZrXFxcnPz8/K7bn5cZM2YoKCjIsYSGhrp8OwAAAAAA+LdcHryjoqLUq1cvffrpp6pZs6YkqUKFCoqIiMg1NiIiQlWqVLluf17Gjx+vxMRExxIdHe3aDQEAAAAAwAVcGryTk5PVtWtXPf/88+rataujvXTp0vLx8dHx48cdbVlZWVqzZo3atGmjZs2aadOmTcrKynL0//LLL7Lb7Xme+y1Jvr6+CgwMdFoAAAAAAChoXBa8s7Oz1bdvX7Vs2VKjRo3K1T9mzBgNHjxYZ8+eVXJyskaOHKm2bduqcuXKCgkJ0X333acxY8YoJSVF0dHRGjJkiCZMmOCq8gAAAAAAcAuXBe+RI0dqw4YNmjt3rry9vR1LmzZtJElPPfWU2rVrp3vuuUchISHKyMjQ3LlzHet/9NFHio+PV9myZdWoUSP17t1bgwYNclV5AAAAAAC4hYdhGIa7i3CFpKQkBQUFKTExsdBNO6/04rfuLuG2c+b1LtcfBAAAAADXcKM51LTbiQEAAAAAAII3AAAAAACmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjeA29bJkyfVuXNnBQUFKSwsTEuWLHH0LV26VLVq1VJgYKDat2+vU6dOOfqSk5M1bNgwlSlTRuXKldP48eOVmZnpjk0AAABAIUDwBnBbSk1NVceOHdW7d2/FxMRo2bJleuWVV7Rp0yatX79eU6dO1ZIlSxQTE6M+ffqoS5custlskqTBgwcrJydHx44d0/79+/XLL79o2rRpbt4iAAAAFFQehmEY7i7CFZKSkhQUFKTExEQFBga6u5x/pNKL37q7hNvOmde7uLsEuNnGjRv14YcfavXq1Y62r776SqtWrVJWVpYefvhh9ezZ09HXo0cPPfPMM2ratKkqVaqk8+fPy8vLS5IUHx+vu+++W5GRkfm8FQAAAHCnG82hHPEGcFvKzs7Osz0hIeGafTk5Ocrr+8r4+HiX1gcAAIBbB8EbwG2pefPm2rdvn+bPn6/09HQdOnRIL7zwglq2bKk+ffpo/Pjx+umnn5Senq6PP/5Y69ev13333aeAgAA1bNhQI0eOVEJCgv744w+Fh4erRYsW7t4kAAAAFFA3FbxbtWolT09Pvf32207tO3bsUP369WW1WtWwYUPt3bvXqf/jjz9WhQoV5O/vr169eik2NtbRl5mZqWeeeUbFihVTiRIl9PzzzysrK+tmygOA6woMDNQ333yjefPmqVy5cmrTpo0uXbqkJ598Un379tWTTz6pHj16qGrVqho2bJjCw8NVrlw5SdLChQt18eJFVatWTffcc4++/fZbvfTSS27eIgAAABRUNxW8N2/erEmTJjm1xcbGqlevXpo0aZKSkpL08ssvq0ePHoqJiZEkbdiwQdOnT9fatWt18eJF1alTR7169XKsP3HiRP3+++86duyYjh07pqNHj2rixIn/YtMA4Nruuece7dy5U5GRkbJYLJo1a5aCg4MlSWPGjNGZM2f07rvvqlSpUnrjjTcc65UqVUrLly9XXFyc7r33Xg0aNEjNmzd301YAAACgoHPZVPPPPvtMDz/8sHr37q0iRYqoZ8+eCg8P1wcffCBJmjVrlmbOnKm6devKarVq2rRpysnJ0Q8//KCMjAzNmzdPCxYsUJkyZVSqVCktWrRIn3zyiVJTU11VIgDk6eWXX9Y999yjfv36ObUnJydrzJgxmj17tooXL55rvZUrV+rw4cO5Zv8AAAAAV3JZ8N62bZt69Ojh1NanTx9t2rRJhmFoz5496tKlS579hw8fVs2aNVW2bFlHX4kSJdS4cWPt3LnTVSUCQC4HDhzQkiVLNHfu3Fx9EyZMUJMmTdSnT59cfSkpKRo9erTmzp2roKCg/CgVAAAAhZS3q54oKipK1apVc2oLCwvT6dOnFRcXp+DgYFksllz9S5cuzXPdK9fPi91ul91udzxOSkpywVYAuJ3k5OToqaee0uuvv67y5cs79R06dEhffPGFfv755zzXnTRpklq0aKFu3brlR6kAAAAoxFwWvNPT0+Xn5+fUZrValZ6enmffP+nPy4wZM/TKK6+4pngApiuI96vPybApyXqnpp8O0fS/1Wf/47jUfIiavHsgz3UTDyUq4K6uBXK7LuN+9QAAAAWDy6aaW61W2Ww2p7a4uDj5+fnl2fdP+vMyfvx4JSYmOpbo6GjXbAiA24anj0XB9/0nzz7fcmHyq3HfVdcNatxbXn5MMQcAAMD1uSx4V6hQQREREU5tERERqlKlikqUKKFLly4pMzMzz/681r2yPy++vr4KDAx0WgAAAAAAKGhcFrybN2+uDRs2OLWtWLFCbdu2lYeHhxo0aKAffvghz/769evr6NGjSkhIcPTFx8drz549uu++qx9xAgAAAACgoHNZ8B40aJAWLlyo9evXKysrS2vXrtWyZcs0fPhwSdLYsWM1evRoHTt2TDabTdOmTZPVatUDDzwgHx8fDRgwQEOGDFFcXJwuXryogQMH6umnn77qVHMAAAAAAAoDlwXvMmXK6Msvv9T48eMVEBCgKVOmaPXq1SpdurQkqWPHjho9erTatWun4sWL6+DBg1q5cqVj/alTp+qOO+5Q1apVVaNGDVWvXl1TpkxxVXkAAAAAALiFh2EYhruLcIWkpCQFBQUpMTGx0J3vXZCvinyr4mrP+Y/9PP+xnwMAAJjrRnOoy454AwAAAACA3AjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiVwavOPi4vTYY4+pePHiqlChgmbOnOno++2339S8eXNZrVbVrl1b69atc1p39erVqlGjhqxWq1q3bq0TJ064sjQAAAAAANzCpcE7PDxc1apVU3R0tPbt26dt27Zp4cKFstvt6ty5sx555BElJiZq7ty5Gjx4sI4cOSJJOnLkiIYOHap58+YpMTFRffv2VceOHWWz2VxZHgAAAAAA+c6lwXvr1q166aWX5O/vrzJlymjkyJH66quvtGrVKtWpU0cjRoyQj4+PWrRooUmTJumtt96SJM2ePVvjxo3T/fffLx8fHz311FNq2LChli5d6sryAAAAAADIdy4N3l26dNG4ceOUlJSk6OhoTZ8+XWXKlNG2bdvUo0cPp7F9+vTRpk2bJOm6/QAAAAAAFFYuDd5z5szRypUrFRQUpAoVKuj8+fOaPHmyoqKiVK1aNaexJUuWlM1mk91u17lz51SlShWn/rCwMJ0+fdqV5QEAAAAAkO9cFryzsrLUrVs3Pfroo4qLi1NkZKQ6duyoP//8U+np6fLz88u1jtVqVXp6unJycuTp6Zln39XY7XYlJSU5LQAAAAAAFDQuC95r166V1WrVG2+84biq+bRp0zRgwAD5+PjkeaG0+Ph4+fn5ydPTU4ZhOPXFxcXlGdYvmzFjhoKCghxLaGioqzYFAAAAAACXcVnwPn78uFq0aOHU5u/vr+DgYElSRESEU19MTIyKFy8uHx8fhYSEKCoqyqk/IiIi1/TzK40fP16JiYmOJTo62jUbAgAAAACAC7kseFepUkXHjh1zarPZbPrtt9/02GOPacOGDU59K1asUNu2bSVJzZs3v2Z/Xnx9fRUYGOi0AAAAAABQ0LgseHfr1k0HDx7UnDlzlJycrHPnzik8PFxNmzbVgw8+qL1792rRokXKzMzUrl279Oabb+r555+XJI0cOVKvvvqq9uzZo8zMTH322Wf6+eef9cgjj7iqPAAAAAAA3MJlwdtisWjt2rX6+uuvVaZMGTVu3FilS5fWokWLZLFY9M033+jjjz9W0aJFNWjQIH388ceqXbu2JOmuu+7S+++/r8cff1yBgYFavHix1q1bJ19fX1eVBwAAAACAW3i78smqV6+ujRs35tlXq1Ytbd++/arr9uzZUz179nRlOQAAAAAAuJ1L7+MNAAAAAACcEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATmRq8IyMjtXDhQjNfAgAAAACAAs3U4D1q1CjFxsY6Hu/YsUP169eX1WpVw4YNtXfvXqfxH3/8sSpUqCB/f3/16tXLaV0AAAAAAAoj04L3unXrdOrUKY0dO1aSFBsbq169emnSpElKSkrSyy+/rB49eigmJkaStGHDBk2fPl1r167VxYsXVadOHfXq1cus8gAAAAAAyBemBG+73a7Ro0dr7ty58vb2liR99tlnevjhh9W7d28VKVJEPXv2VHh4uD744ANJ0qxZszRz5kzVrVtXVqtV06ZNU05Ojn744QczSgQAAAAAIF+YErzffPNNtWzZUs2aNXO0bdu2TT169HAa16dPH23atEmGYWjPnj3q0qVLnv0AAAAAABRWLg/e0dHRmjFjhjZu3KhixYrp2WefVU5OjqKiolStWjWnsWFhYTp9+rTi4uIUHBwsi8WSZz8AAAAAAIWVy4P3tGnT1K5dOx04cEAHDx7U9u3bNWfOHKWnp8vPz89prNVqVXp6ep59V/bnxW63KykpyWkBAAAAAKCg8Xb1E65Zs0bHjh1TsWLFJEmffvqp+vbtK6vVKpvN5jQ2Li5Ofn5+efZd2Z+XGTNm6JVXXnF1+QAAAAAAuJRLj3hfuHBB/v7+jtAtSbVr19bZs2dVoUIFRUREOI2PiIhQlSpVVKJECV26dEmZmZl59udl/PjxSkxMdCzR0dGu3BQAAAAAAFzCpcG7RIkSSkhIUEJCgqPt6NGjqlChgpo3b64NGzY4jV+xYoXatm0rDw8PNWjQINcVzC/358XX11eBgYFOCwAAAAAABY1Lg7enp6f69++v/v37688//1RERIQGDx6sUaNGadCgQVq4cKHWr1+vrKwsrV27VsuWLdPw4cMlSWPHjtXo0aN17Ngx2Ww2TZs2TVarVQ888IArSwQAAAAAIF+5/Bzv119/XS+88ILq1Kkjf39/PfPMMxoyZIgk6csvv9SIESPUq1cv1alTR6tXr1bp0qUlSR07dlRkZKTatWunuLg4dejQQStXrnR1eQAAAAAA5CsPwzAMdxfhCklJSQoKClJiYmKhm3Ze6cVv3V3CbefM612uPwguxX6e/9jPAQAAzHWjOdTltxMDAAAAAAD/D8EbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQC4hUVERKhjx44qWrSowsLCtGzZMkffli1b1KBBAwUEBKhp06bav3+/oy8nJ0cvv/yyypYtq5IlS2rYsGFKS0tzxyYAAFDoEbwBALhFGYah7t27q3Xr1rp48aKWL1+u8ePHa/fu3YqKilJ4eLhmzZqlhIQEzZw5U0888YTi4uIkSTNnztS2bdt08OBBnTx5UmlpaXr++efdvEUAABROpgbvt956SxcvXpQk/fbbb2revLmsVqtq166tdevWOY1dvXq1atSoIavVqtatW+vEiRNmlgYAwC3v0qVLevrppzVu3Dj5+vqqXr166tGjh7Zv3669e/eqZcuWatGihYoUKaL77rtP9957r7Zt2yZJKl++vBYvXqxy5copODhYY8aM0Y8//ujmLQIAoHAyLXj//PPPmjhxoiTJbrerc+fOeuSRR5SYmKi5c+dq8ODBOnLkiCTpyJEjGjp0qObNm6fExET17dtXHTt2lM1mM6s8AABuecWKFdPQoUMlSRkZGfr++++1cuVKtW7dWs2aNdO2bdu0fv16ZWRk6LvvvtPXX3+tMmXKSJIeeeQRVahQQYZh6PTp05oyZYo6dOjgzs0BAKDQMiV4Z2Rk6PHHH1dWVpYkadWqVapTp45GjBghHx8ftWjRQpMmTdJbb70lSZo9e7bGjRun+++/Xz4+PnrqqafUsGFDLV261IzyAAC47TRu3Fjt27fXAw88oLvvvlt33HGH3nzzTXXu3Fm+vr7q0KGDBgwYoKZNmzqt99///ldVq1bVrl27NHbsWDdVDwBA4WZK8H755Zd11113qXz58pKkbdu2qUePHk5j+vTpo02bNt1QPwAA+Hd27dqlXbt26fjx45o+fboOHDig5557Tt9++63S0tL03XffydvbW3a73Wm9Z555RlFRUXr88cfVvn17ZWRkuGkLAAAovFwevLdu3aoVK1Zozpw5jraoqChVq1bNaVzJkiVls9lkt9t17tw5ValSxak/LCxMp0+fvurr2O12JSUlOS0AACBvFotFTZo00VdffaV33nlH06ZN0/Tp09W5c2dZrVa1a9dOjRo10ssvv+y0noeHh0JDQ/X2228rJCRE69evd9MWAABQeLk0eCclJal///6aP3++goKCHO3p6eny8/PLNd5qtSo9PV05OTny9PTMs+9qZsyYoaCgIMcSGhrqug0BAOAWcObMGZ0/f96pLSQkRF5eXvrpp5/UokULp77GjRtr48aNSktL0+HDh3M9X7169XI9HwAAuD6XBu9nnnlGDz74oB544AGndqvVmueF0uLj4+Xn5ydPT08ZhuHUFxcXl2dYv2z8+PFKTEx0LNHR0S7ZBgAAbhU7duzQc88959R25swZFS1aVLVq1dKxY8ec+g4ePKiyZcvKy8tL7du3zzWbbN++fapVq5bpdQMAcKtxWfBes2aNlixZovfff18Wi0UWi0WRkZEqX768fv31V0VERDiNj4mJUfHixeXj46OQkBBFRUU59UdEROSafn4lX19fBQYGOi0AAOD/6dmzp/bu3auFCxcqPT1dx44d03/+8x9NnDhRY8aM0ciRI7V7927Z7XZt3bpVo0aN0ogRI+Tr66v+/ftr4MCBiomJUWJioiZPnixJatmypZu3CgCAwsdlwbtHjx7KzMyUzWZzLBUrVtTZs2f12muvacOGDU7jV6xYobZt20qSmjdvfs1+AADwz/n7+2vt2rVavHixSpUqpfbt2+vRRx9V//791bZtW02YMEGPP/64goODNXLkSL355pvq2bOnJOnVV19V5cqVdffdd6t8+fL6/ffftWLFCvduEAAAhZSH8fc53i5UqVIl7d+/XwEBAapdu7YmT56sRx55RPv379fDDz+s9evXq3bt2jpy5Ig6d+6sFStW6J577tHnn3+u119/XUeOHJGvr+8NvVZSUpKCgoKUmJhY6I5+V3rxW3eXcNs583oXd5dw22E/z3/s5wAAAOa60RzqnR/FWCwWffPNN3ryySf15JNPqkqVKvr4449Vu3ZtSdJdd92l999/X48//riio6PVtGlTrVu37oZDNwAABQFfMOU/vmACABQGpgbvM2fOOH6uVauWtm/fftWxPXv2dExvAwAAAADgVuHy+3gDAAAAAID/h+ANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYyKXBOyEhQeHh4SpVqpQqVaqk119/XTk5OZKkHTt2qH79+rJarWrYsKH27t3rtO7HH3+sChUqyN/fX7169VJsbKwrSwMAAAAAwC1cGrz79OmjkJAQnTp1St9//71Wr16t2bNnKzY2Vr169dKkSZOUlJSkl19+WT169FBMTIwkacOGDZo+fbrWrl2rixcvqk6dOurVq5crSwMAAAAAwC1cFrwPHTqkP//8U6+99poCAwNVvXp1zZ8/X5988ok+++wzPfzww+rdu7eKFCminj17Kjw8XB988IEkadasWZo5c6bq1q0rq9WqadOmKScnRz/88IOrygMAAAAAwC1cFryzs7M1duxYeXh4ONpCQ0MVGxurbdu2qUePHk7j+/Tpo02bNskwDO3Zs0ddunTJsx8AAAAAgMLMZcG7QYMGGjBggFPb2rVr1aBBA0VFRalatWpOfWFhYTp9+rTi4uIUHBwsi8WSZz8AAAAAAIWZaVc1j4mJ0bPPPqtJkyYpPT1dfn5+Tv1Wq1Xp6el59l3ZfzV2u11JSUlOCwAAAAAABY0pwdtut+vBBx/U8OHD1bhxY1mtVtlsNqcxcXFx8vPzy7Pvyv6rmTFjhoKCghxLaGioy7cDAAAAAIB/y5TgPWjQIIWGhuqll16SJFWoUEERERFOYyIiIlSlShWVKFFCly5dUmZmZp79VzN+/HglJiY6lujoaNdvCAAAAAAA/5LLg/eUKVN0+vRpLViwwHGhtebNm2vDhg1O41asWKG2bdvKw8NDDRo0yHUF88v9V+Pr66vAwECnBQAAAACAgsbblU+2ZMkSff7559q1a5fTxdIGDRqku+++Wy1btlS7du20YcMGLVu2TAcPHpQkjR07VqNHj9ZXX32lSpUq6a233pLVatUDDzzgyvIAAAAAAMh3Lgve27Zt08CBA5WZmaly5co59Z06dUpffvmlRowYoV69eqlOnTpavXq1SpcuLUnq2LGjIiMj1a5dO8XFxalDhw5auXKlq0oDAAAAAMBtXBa8W7RoIbvdftX+ihUr6vDhw1ftHzp0qIYOHeqqcgAAAAAAKBBMu50YAAAAAAAgeAMAAAAAYCqCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAOCWkZCQoPDwcJUqVUqVKlXS66+/rpycnFzjMjMzNXHiRDdUCOB2RPAGAADALaNPnz4KCQnRqVOn9P3332v16tWaPXt2rnGTJk3SoUOH3FAhgNsRwRsAAAC3hEOHDunPP//Ua6+9psDAQFWvXl3z58/XJ5984jRux44deuedd9xUJYDbEcEbAAAAt4Ts7GyNHTtWHh4ejrbQ0FDFxsY6HqekpCg8PFzPPfecO0oEXKpVq1by9PTU22+/7dS+bNkyhYWFqWjRourUqZNOnz7tpgpxGcEbAAAAt4QGDRpowIABTm1r165VgwYNHI9HjRqlLl26qF27dvldHuBymzdv1qRJk5za9uzZo2effVZLly7VxYsX1bVrV3Xr1s1NFeIygjcAAABuSTExMXr22WcdwWTNmjXavXu33njjDTdXBpgnMzNTy5cv17333itfX1+NGDFCf/zxhy5evOju0m5r3u4uAAAAAHA1u92uBx98UMOHD1fjxo31559/asSIEfrmm29ksVjcXR5gmubNmzt+jo+P13vvvaeqVauqRIkSbqwKBG8AAADccgYNGqTQ0FC99NJLkqRhw4YpNjZWTZs2lSTl5OQoOztbZcuWVUxMjDtLBUzx008/qX79+vL09NS6deucrn2A/MdUcwAAANxSpkyZotOnT2vBggWOsLFy5UplZmbKZrPJZrPpu+++U6dOnQjduGXVq1dPFy5c0Lx58/TEE0/o999/d3dJtzWCNwAAAG4ZS5Ys0eeff67Vq1czpRy3vZIlS2rgwIEaNWqUPvzwQ3eXc1sjeAMAAOCWsG3bNg0cOFAREREqV66cvL29HUtkZKS7ywPyxZ49e5Sdne3UVq9ePZ0/f95NFUEieAMAAOAW0aJFC9ntduXk5CgrK8tpqVixotPYBx54QGvXrnVTpYB5JkyYoB9++MGpbd++fapVq5abKoLExdUAAADwD1R68Vt3l3DbOfN6F3eXgEJkzJgxGj16tJYtW6bq1avrm2++0fz583XgwAF3l3ZbK1BHvJOSktSvXz8FBASoXLly3GMRAAAAAP6Bzp076/nnn1fv3r0VHBys9957T6tXr1bJkiXdXdptrUAd8X7yySdlsVh07tw5Xbp0SX369FFwcLCGDh3q7tIAAAAAoMCZMmVKrrb+/furf//++V4Lrq7ABO9z585p8+bNioyMlMViUVBQkBYtWqROnToRvAEAAADkG06pyH+3+ikVBWaq+Y4dO9SuXTun2z7UrFlTAQEBOnHihBsrAwAAAADg5hWY4B0VFaVq1arlag8LC9Pp06fdUBEAAAAAAP9egZlqnp6eLj8/v1ztVqtV6enpudrtdrvsdrvjcWJioqS/LtBW2OTY09xdwm2nMO4nhR37ef5jP89/7Of5j/08/7Gf5z/28/zHfp7/Cut+frluwzCuOa7ABG+r1aq0tNw7eFxcXJ6BfMaMGXrllVdytYeGhppSH24tQe+6uwLAfOznuB2wn+N2wH6O20Fh38+Tk5MVFBR01f4CE7wrVKig9evX52qPiIhQlSpVcrWPHz9eY8eOdTzOyclRfHy8SpQoIQ8PD1NrxV+SkpIUGhqq6OhoBQYGurscwBTs57gdsJ/jdsB+jtsB+3n+MwxDycnJKleu3DXHFZjg3axZMz333HPKysqSt/dfZf3yyy+y2+15nvvt6+srX19fp7bg4OD8KBV/ExgYyAcbtzz2c9wO2M9xO2A/x+2A/Tx/XetI92UF5uJqISEhuu+++zRmzBilpKQoOjpaQ4YM0YQJE9xdGgAAAAAAN63ABG9J+uijjxQfH6+yZcuqUaNG6t27twYNGuTusgAAAAAAuGkFZqq59Nch+iVLlri7DNwgX19fTZ48OdeUf+BWwn6O2wH7OW4H7Oe4HbCfF1wexvWuew4AAAAAAG5agZpqDgAAAADArYbgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4I2blpqaqrp16yorK8vRtmXLFr388stObUBhlpKSosDAQKd9et26derXr58yMjLcWBnwzyQmJmrUqFFX7ff399eFCxccj1NTU/OjLAAAbgvcTgw3LSsrSxaLRenp6Vq6dKnCw8O1ZcsWtWnTRomJiQoICHB3icC/lp2dLV9fX6WmpurNN9/UxIkTtW3bNj3wwAPs5yhUkpKSVLt2bUVHR2vevHlKS0uTh4eHrFarhgwZopIlSyoqKkp+fn6KjY3VPffco507d6pixYruLh34V9atWyc/Pz95euY+3uTh4aGyZcuqevXqbqgMcL2srCw9+eSTeu+991S0aFEdOXJEnp6eql27trtLu+0RvHFdqampat++vXx9fSVJhmEoKChIq1evVkBAgOLj41W2bFnFx8fr8OHDuvfee5WUlCR/f383Vw7cuJSUFIWFhTnt5yVKlND+/ftVtGhRx34eFxenn376Sffccw/7OQoVu92uOnXq6MSJE7rzzjvVokULSdLmzZt18uRJVaxYUZGRkZKkOXPm6NNPP9XBgwfdWTLwr0RFRalChQq644471LBhQxmGoR9//FH333+/Dhw4oDp16sjHx0fbtm3TkSNHVKFCBXeXDNwQu92uDz/8UFarVV5eXkpLS1OvXr3Upk0bHTx4UMHBwbp06ZICAgL06KOPaufOnTpx4oSKFCni7tJva0w1x3X5+voqOjpagwYN0smTJzV48GD9/vvvkiSLxSIfHx95e3s7HkuSj4+P2+oFbobVapXFYtHnn38uDw8PLV68WGlpaZL++gwUKVLEsZ9f3r8vh3SgMPD29nbah+fNm6d58+bJy8vL0da9e3fFxsZq5cqVeu6559xZLvCvNW3aVIsXL5afn5++/vprffPNNypfvry++eYbNW7cWAsWLNDatWs1YMAAx7/3QGFgGIbGjh2rJUuWaOHChRo7dqzsdrtOnz4ti8UiX19f+fr66ptvvtHKlSv1ySefELoLAG93F4CCz9vbW8HBwerXr5/eeOMN9evXTzNmzHD0SXJ8mDMzM1WkSBE+3Ch0vLy85O/vr2bNmjn+e3la4t8Dd0ZGhiwWi6MdKAy8vLwUGxur4cOHKyYmRsOHD5ckp/28devWatGihRISEvTggw+6s1zgX7NarVqzZo0iIyM1depUSdLFixc1depUHT9+XO+8844CAwPl5+enO++8083VAjfO19dXXl5e2rp1qyTJz8/P6SCBp6en5s+frwkTJmjp0qVq27atmyuGRPDGTbr8h5rdbtfUqVOVkpKiqVOn6ty5cypbtqybqwNc4/J+np6eroEDByohIUEDBw7UhQsXdMcdd7i5OuCfs1qtatasmdatW6dmzZrJMAxt3rxZ0l/nuo4ePVrJyclat24dMzpQaO3fv1/ffPONfH199eWXX6pixYqOmR0eHh7y8vJy/NfT01N2u93NFQP/jIeHhzw8PJzaLu/PEyZMUGZmpnbs2KG9e/eqUqVK7ikSuTDVHDfl8qUBcnJydOLECXXv3l0nTpzQ4cOHVa9ePTdXB7jG5f3c09NTISEhGjNmjEJCQpSRkaEGDRq4uTrgnwsKClK/fv1UrFgx9evXT4899pgkafTo0UpKSpIk/fHHH/r555916NAhd5YK3LTMzEx99913ioyM1NmzZ+Xh4aGBAweqf//+CgoK0oABA1SxYkU9/fTTmjBhgmbOnOnukoF/7O+X6crJyZFhGDp16pSys7O1Zs0aLV68ONc4uA9HvHFTLn+IrVarPv/8c0d7586dHX/IAYXd5f3cx8dH06ZNc7Q1a9ZMY8eOdWdpwE05c+aMGjVqpBMnTqhRo0aO9tKlSyshIUHr16/Xjz/+qCFDhmjFihW6++673VgtcHOaNm2qXbt2adasWerYsaO8vb3VpEkTxyympk2bKj4+XmFhYWrTpo2mTp3Kvo5CJScnJ9cR76ysLGVnZ+uLL77Q119/rS1btuiJJ57QiRMntHDhQjdViitxxBvXlZ2drYyMDP3++++O/16+p3FWVpaOHDmi3377Ta+//rpsNpseeughN1cM/HPZ2dlKSUnRd9995/jv5f08OztbO3fu1MaNGzVixAhVrlxZHTp0cHPFwD9XtmxZff7556pQoYIWL16sRYsWyTAMvfTSSypXrpwmTJggi8WiHj16aMeOHe4uF7hpFy5c0LFjx/TBBx/o5MmTioyMVEREhCIiIhQZGank5GT99ttvatSokVq3bq19+/a5u2TghtlsNmVlZTmdLpGcnKzMzExlZGQoMzNTd955p7Zs2aLNmzfr448/dnfJEEe8cQNsNpt+//131axZU4Zh6M4771T58uUl/XWO96FDhzR06FAFBARo9+7dbq4WuDnp6emy2WwaOnSoJGno0KEqXry4pL8+A5cvRpWdna0NGza4s1TgpuTk5Mjb21thYWGOc1w9PDyUk5Mj6a8vUrdt26bvv/9e5cqV008//eTmioGb5+npqa+//lofffSRJKlx48aKjY11upe33W5Xx44dtWLFCs6DRaHi6+urI0eOOP4tz87OVvny5fX+++8rIyNDWVlZSk1NldVq1Zw5czRgwAD169ePW6C6Gffxxg25fLXyyzIyMuTt7S2LxaKMjAzFxcVp1qxZ+vDDDzVhwgSNGTPGjdUCrpOdnS2LxaLMzExlZ2dr/vz5evHFF9WvXz+9+eabXIAKhYbNZlPNmjUVERGhli1bKjY2VpmZmSpTpox27dql8uXL68yZM/L29tbFixdVunRpxcXFqVixYu4uHfjHUlJSVKFCBS1YsECtWrVS+/btdf/992vkyJGS/jptqFGjRjp69KiCg4PdWyxwk/7v//5PvXr1ynUb39jYWG3fvl2jRo3S+vXr9euvv+o///mPm6rEZQRv3LS0tDQFBAQoMzPTcbXQXbt2aeDAgdq+fbtKlCjh5gqBfy8lJUWBgYGOL5sk6dSpUxo0aJC+/fZbvj1GoREfH6+qVasqISEhz/6goCBFR0crMDBQycnJWrRokZ588kluD4lCKSkpSeXKlVPz5s31008/KTk5WXXr1nW6MOb8+fM1YMAASdJ///tfd5UK/GNRUVF68MEHdfjwYa1YsUJpaWmaMWOGLBaLY4xhGPr999/l7e2t5cuXq02bNm6sGBJTzXGDsrOzde7cOYWGhjou5mCxWHTkyBGnaVtNmzbVgQMH5Ofn565SAZcKCAhQcnKy0z27q1atqs2bN+e6sAlQkBUvXvyqoVuSli1bJqvVKkkqWrSoRowYkV+lAS6XmpoqX19fbdiwQdnZ2frhhx80e/ZszZ49W126dFHPnj317rvvKiUlRXFxce4uF/hHypYtqwYNGmjZsmWqWrWqli5dqrS0ND377LNO47Kzs7Vnzx7HKUVwL45444ZER0erUqVKiomJUalSpZz6Bg8erLvuukujRo1yU3UAAAD/j81m08GDB3Xfffc5tW/evFmLFy/W+++/z0EC3DI2btyotWvX6v3333d3KbgGgjduSHx8vEqWLKnk5GSnqbVPPfWU5s+frw8//FADBw50Y4UAgBtx4cIF3Xvvvfrpp5+uev52dHS0Bg0apO+++y6fqwMA4NbE7cRwQ3x9feXh4eF08YZnnnlGK1as0P/+9z9CNwAUAsnJybJarTp79qysVquio6N18eJFXbhwQVFRUbpw4YKmT58uLy8v7d+/393lAqb6888/dc899+j48ePuLgW4Kenp6Vq1apUkqUKFCoqOjnZzRbgWgjduyOWL61w+z3XVqlWaP3++1q1bpxYtWrizNADADVi4cKGee+45WSwWeXh4yGKxqEaNGipTpozKli2rypUra82aNZoxY4YCAwOdLtIDFDaHDx9WYGCg/vjjD0lSYmKixo0bp4sXLzrGWK1WHT58mOt1oNDKzMzU008/LUny8fFRyZIltWPHDnXo0EGdO3dW586d1a5dO3Xt2tXNlUIieOMGeXl5yTAMLVmyRJLUo0cP/e9//1OjRo3cXBkA4Eb8/vvvjnt5X74oZqVKlZSdna1GjRrps88+k7+/v0qUKCFfX1+nCwoChY2fn59SUlIcp8f5+Pho5syZSktLc4y5/OXS32/FBBR02dnZql27trp3766EhAS1bt1a58+fl6+vr6xWqxISEnTnnXeqdevWOnTokF566SV3lwxxVXP8Q6NGjdI777yjOnXqSJLmzJnj1J+VlaVLly5p3bp17igPAHAVdevW1bfffivp/wWNK+9Df/l0oqJFi8rb25vgjULt8syOy1fqt1qtMgzDab++/PPlW6IChUVmZqYmTJggf39/DR8+XC+88IIGDRokT09PWa1WlShRQnfeeaeqVq0qHx+fXBcZhHtwxBs3zMPDQ8ePH1ejRo20ZMkS7d69W5mZmU5LRkaGMjIy3F0qAOBvqlSpooiICG3dulWStHXrVqWlpWnr1q1KSkrSsWPHdOLECdlsNm3bts3pVpFAYXP5FLkr70Pv4eHhNK388s/s6yhsLBaLWrdurS5dusjPz08dOnRwXKWfUycKLr7Oxg25fPH7kiVLau7cuWrevLlGjBihwYMHq02bNm6uDgBwPWXKlNGhQ4f07LPPKiMjQ88++6zOnTunZ599VlFRUVq2bJm8vb11/vx5Pfvss4QRFGqenp4yDMPpbxTDMNSnT59cMz2AwiYzM1N33HGHvL29lZ2drSJFiignJ0eZmZmy2WxKT09XXFycAgIClJ2drejoaIWGhrq77NsewRs3JCsrS9Jf55R4eXnpscceU2BgoHr16qXvv/9ejRs3dnOFAIBrKV68uCpUqKB9+/YpICBA+/btU/369bVv3z41bdpUw4YNU7FixfTyyy9r3759qlq1qrtLBv61K/8++fvfKoZh6McffyR8o9Dx9PRUdHS04xodp06dUvXq1ZWSkqK4uDidO3dOixYtkiQVK1ZMzZo1U1RUlJurBsEbNyQzM1PSXwH88rlQ3bt319NPP62HHnromveDBQC4n9Vq1aVLlyT99SXqlf+9LCcnR2lpaTIMQzk5OfldIuAyhmHIw8NDM2bMuOa4N9980zGrDygsvLy8FBISovT0dH388cfy9/fX4MGDHUH87bffVseOHbVjxw61bt3a3eXi/8c8MtwQm80mSbLb7U7t06ZNk9VqVXh4uDvKAgDcIC8vL6Wnp8swDMeXqfHx8Zo0aZLOnj2rVatWKT09XQkJCbLb7Y6ZTkBhdOVMPUnatWuXoqKici0eHh4EbxRahmFowIABOnfunFJTU1WyZEllZ2dr9OjR8vX11fTp0/Xll1+6u0z8/zjijRuSkZGhWrVqOf5Yu8zLy0uTJk3S+vXrlZOTwzmBAFBAZWZmKicnRzabTYZhKDs7W/3795eHh4cGDhwom83mOGcwJSUl1xetQGFyef+12+2y2+1q1qyZU8i+/LOHh0eumR9AQZeTk6PWrVtr3Lhxjrbt27dr0aJFys7Ols1m06JFi3Tvvfdq0KBBqlWrlmrXru3GiiERvHGDQkJCdOTIkTz7Hn30UfXt25fQDQAFmGEYWrFihVJTU2UYhlJTU/Xaa6/lGhcbG6vIyEilpqa6oUrANVJSUmQYhlJSUlS8eHGdPHnS6aJq0l9fRlWtWpXZHSh0UlJSdPfdd6tv377y8vJSamqqoqOj9dVXXzn2+6+++kqSdMcdd+ijjz7Sf//7XzdXDQ+D+TUAANwWsrOzdfz4cW3fvl3h4eG5gshlqamp2rFjh9q3b5/PFQKukZqaql9++UX33HOP0y3FrhQXF6dSpUrp559/Vp06dfK5QuDfO3v2rAYNGqTExEQNHTpUAwYM0Pnz59WwYUOdPXtW0l+zVn18fNxcKSSCNwAAt43o6GhVqlRJMTExKlWqlFPf4MGDddddd2nUqFFuqg7IX5mZmfr9999VrVq1q34JBRQG7733ngYNGqSAgADZbDYdP35c9erVc3dZ+BvmBgMAcJvw9/eXYRjy8/Nzan/qqaf0+eefq2jRom6qDMh/RYoUUe3atQndKPRGjRqlgIAASZLFYiF0F1AEbwAAbhO+vr7y8PBwmnb4zDPPaMWKFfrf//6ngQMHurE6wLWKFy+eq61Pnz7aunWrG6oBXC87O1unT5+WJCUlJSkwMFAxMTFOY86ePavo6Gh3lIe/IXgDAHCbuHyuq7f3X9dWXbVqlebPn69169apRYsW7iwNcLng4GAZhqGoqChJUnp6utatW5frDi1AYZWUlKTq1asrKytLfn5+SklJcZq59Mknn6hOnTqaMmWK+4qEA+d4AwBwm8jOzlaRIkW0aNEiPfbYY8rOztb+/fvVuHFjd5cGuFRycrKqV68uHx8f1a5dW+vXr9f8+fM1ffp07d27V/3795eXl5cMw1BwcLDmz5/v7pKBfywzM1MBAQGO2+d5e3vLZrMpJSVFAwcO1Lp161StWjUdOHCAUyoKAG4nBgDAbWbUqFF65513HFdynjNnjlN/VlaWLl26pHXr1rmjPOBfiY2NVbNmzSRJGzZsUK1atZSQkKBJkyZpxIgR8vDw0Pbt2/XOO+9o/Pjx+uCDD9xcMfDPpaWlyc/Pz+nUIU9PT3l7eys6OlpZWVnatWuXunbtSuguIJhqDgDAbcTDw0PHjx9Xo0aNtGTJEu3evVuZmZlOS0ZGhjIyMtxdKnBT/P399eyzz8rHx0fLli1TcnKy+vTpo/79+2v58uWKi4uTv7+/wsPDFRQUpJ49e7q7ZOAfMQxDlStXVqNGjWSz2dSoUSM1atRI2dnZ2rx5sywWi77++mvdfffdiouLU3p6urtLhjjiDQDAbePy2WUlS5bU3Llz1bx5c40YMUKDBw9WmzZt3Fwd4BoBAQEaNmyY7rrrLs2ZM0eVK1fWyy+/rDFjxmjt2rUc/UOhl5mZqRdffFFFixbViBEjNGLECBmGoUGDBundd9/Vzp07tWDBAnXp0kVly5bVyZMnddddd7m77NsewRsAgNtEVlaWpL/O9fby8tJjjz2mwMBA9erVS99//z3neuOWMmDAAK1du1bHjx/X7t27ZRiGPDw85OHh4e7SgH/Fx8dHY8aMUVZWlkaMGKHw8HBH8F6+fLlWrFihkSNHasOGDSpevLiOHz9O8C4AmGoOAMBt4vLVnC8HcEnq3r27nn76aT300ENKSEhwV2mAy1ksFsXExOitt95SUlKSxo8fL0mcRoFbRmJiojIzM2W32x3/vmdmZqpfv346evSovL29dfjwYe3evdvNlUIieAMAcNuw2WyS5LgC7mXTpk2T1WpVeHi4O8oCXO67776TJA0bNkzHjh3Tl19+qRUrVqhhw4by9/dXenq6vv76a6WkpOibb75xc7XAzbFarYqMjJSvr6/S09NVrlw5paWlSfrri6dZs2ZpyZIlGjZsmJsrhcTtxAAAuG2cO3dOHTt21JYtW1SiRAmnviVLlmj9+vVatGiRPD35Xh6FV1pamsqUKSObzaYLFy4oODhYkvTtt9/qqaee0s6dO/XII4+oSJEiys7OVlpamvbv3+/eooGb8MQTTyguLk7ffvuttm3bprCwMPn7++vdd9/VQw89pBo1ari7RFyB4A0AAGQYhrKyslSkSBF3lwL8a+fPn9ezzz6r3bt3a82aNY7zW9u1a6cGDRpoxowZbq4Q+HfWrFmjIUOGaM+ePapcubLq1aunwYMHq3Hjxpo0aZK2bNmiKlWqqGvXrmrTpo06dOjg7pJvewRvAAAA3JI+/PBDff7559q5c6ekv+7r/cQTT+j8+fPy8vJyc3XAzcvKytKxY8dUp04d/fzzz+rWrZtOnz7t2K/j4uL02Wefafbs2Ro4cKAmT57s5opB8AYAAMAtKz4+XsWLF3c8PnDggO699143VgS43smTJ1WtWrVc7ZmZmfLy8uIUogKA4A0AAIBbSkpKijZv3qyiRYteM3BkZmYqMzNTHTt2zMfqgH8nOztb77777g2dGuTp6am6deuqZcuW+VAZroXgDQAAgFtKTEyMypUrl+sign8XHx+vGjVq6LfffsunygDX8Pb2VqNGjeTr63vNcTExMTp37pwSEhI4vcLNCN4AAAC4pSQmJqpYsWJKSUmRn59fnmNsNpv8/PyUk5OTz9UB/56fn59OnjypcuXKXXPc8ePHVbNmTR07doyrnLuZt7sLAAAAAFzJ29tbHh4ekv6adv7FF184jgzabDY98cQT8vDwcIwBCpsrj17b7XZ9+OGHjn368nHVESNGqHjx4tq1axehuwDgiDcAAABuKZePZqekpCg7O1vBwcEaOnSoDMPQZ599psTERHl4eMjPz0/Z2dnuLhf4x/z9/XXixAmVK1dOdrtdVqtVjz32mLy8vGQYhj7//HPZ7XZ5e3OctaAgeAMAAOCWcjmIpKSkyGKxyNfXV5mZmZKkokWLKjk5WXa7neCNQsvHx0dHjhxRWFiYDMOQl5eX49SKrKws+fj4cBpFAcN15QEAAHDL8vT0dJpSfuVUXKAwysrKUpkyZZSeni5Jjinml/dzTqMomJh7AAAAgFvKlcHaZrMpOztbjz76qAzDkN1uV3p6Old4RqHl7e2t6OhoxxHtjIwMGYahcePGqUiRIo72rKwsppoXILwTAAAAuKVkZ2c7jvgZhqHZs2c7rm7eqlWra97bGyjoUlJS9Morr2jTpk3at2+fsrOzNXHiRPn6+srT01M5OTmaMGECU80LGM7xBgAAwC0lMTFRxYsX19GjR2W1WvMcY7fbdeedd+rMmTMKDQ3N5wqBmzd06FD9+OOPev7559WvXz9ZLBZ3l4QbQPAGAADALeWPP/5Q+fLlb+h8bg8PDy6whkIlISFBRYsWlbe3t/bu3atOnTrJ39//mutERUXlU3W4GqaaAwAA4JZSunRpXbx4UQEBAdc8lzsjI0Px8fH5WBnw7xUrVszxc6VKlbRo0aKrnsttt9uVkJCQX6XhGjjiDQAAAACAibiyBAAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAADAFDNnzlRqaupNrbt+/Xrt3bvXxRUBgHsQvAEgnxw4cEClSpXSH3/8cUPjK1WqpIsXL5pa05QpU/T222+75LnWrVun+++/X5LUsGFDvf/++26p42rOnDmjOnXq/Kvn2L59uxo3bqzAwEA1adJEu3fvvuF1v//+e3l6esrb29uxxMbG5jn28hVqr1w8PT3Vo0cPSeb+vlz53A888ID2799/zTEXL15UqVKl5OHhcd2x+eFGanaF/Njn//jjD5UqVUoHDhy44XVc+Z6tXr1aixYtkq+vr6MtLi5Ojz32mIoXL64KFSpo5syZea6bkpKip556Sjk5OTdcOwAUZARvAMgnRYsWVY0aNWS1Wt1diim+/PJLPfTQQ5Kk6tWrq3Tp0m6uyLVOnDihvn376rXXXlNsbKzGjRunnj176uzZsze0/q+//qrJkycrKyvLsZQpUybPsU888YTTuIyMDNWsWVMTJkxw5SYVCCVLltSFCxccX9rAdSwWi2rUqKGiRYu69Hlv5D1LT0/X2LFjNXfuXKfbHIWHh6tatWqKjo7Wvn37tG3bNi1cuDDX+lOnTlWnTp3UpEkTl9YOAO7CfbwBIJ/UqFFDO3bscHcZpsjMzNQ333yj6dOnS5KWLl3q5opcb/bs2Ro7dqzatm0rSerdu7f27Nmj5cuXa+zYsddd/9dff3Ws+0+tXLlSFSpUUMOGDW9qfdyeihcv7rZ/c6ZPn662bduqadOmTu1bt27VqlWr5OPjI39/f40cOVLvv/++wsPDHWOOHTumL774QkeOHMnvsgHANBzxBoB8cvHiRVWqVMkx5fno0aN64IEH5OfnpwYNGujgwYOS/gpo3t7eioyMVNmyZTVq1CjHcyxevFi1atWSr6+vqlatqpkzZ8owDEnSli1b1KVLFz322GMqW7asUlNT9cADD2jHjh0aM2aMSpQooTJlyuidd97Js77+/ftr8eLFGjZsmAIDA1WlShV9++23ysjI0DPPPKNixYqpatWqWr9+fa51//e//6lWrVq64447JEldu3bVli1bJOm6NTRp0kRTp07VCy+8oODgYEf7iRMn1K1bNwUEBKhYsWLq16+fzp8/7+ivVKmSPvnkEwUFBWn58uVasGCBnn76aa1evVq1atVSQECAevbsqbi4uFz1btmyRV27dtWXX36pqlWrKjAwUCNHjlROTo6++uor3XnnnQoODtaoUaOUnZ0tSapcubJjqvdloaGhV50u/ndHjx5VWFjYDY29kmEYeu211zRx4sRcfZ999pnuvPNOWSwW1atXT1999dUNPefGjRvVrFkz+fn5qWTJknr00Ud15swZpzEff/yxqlSposDAQA0cOFA2m82p//3331e1atVktVrVsGFDbdq0SX369NGWLVuUmpoqb29v/fjjj2rSpEmu39uN+jf75NUYhqH33ntPNWvWlMViUcWKFfXiiy86nYdst9uv+ZlJTk7W8OHDVapUKfn5+alVq1bas2dPrtfau3evOnTooKJFiyooKEjdunXTTz/9lGtcVlaWHn30UXXr1k02m82xL3/11VeqW7euLBaL7rzzTs2fPz/XuqtWrVK9evXk6+urypUr66233nL8myBJAQEBTj+fO3dO3bt3V0BAgGrWrKnvv/9eklz2nknSyZMntXDhQr3xxhu5+rp06aJx48YpKSlJ0dHRmj59eq6ZH08//bRmzJjh9O8BABR6BgAgX1y4cMGoWLGiERERYZQtW9Zo0KCBsXv3biMtLc2YN2+eUb58eSMjI8MxvmLFisaFCxccjz/66COjWbNmxk8//WRkZGQYR44cMTp06GA899xzhmEYxubNmw2r1Wq8+uqrhs1mMwzDMO6//36jfv36xttvv22kpaUZP//8s1GlShVj3bp1hmEYxuTJk4233nrLMAzDCA8PNypXrmz897//NdLT043//e9/RvHixY3+/fsbs2fPNtLT040ff/zRKFWqlJGSkuK0bQMGDDDee+89x+MuXboYmzdvvqEa/l6HYRhGdHS0UblyZWPZsmVGamqqcfHiReP11183atSoYSQmJjp+P82bNzcuXrxoZGdnG/Pnzzdq165ttGvXzoiOjjbi4+ONIUOGGH379jUMwzAiIiKM2rVrO35X5cuXN7p27WqcPXvWiImJMZo2bWoMHTrU6Nq1q3Hu3Dnjzz//NFq2bGksWLDgqu9phw4djOXLl9/I228EBQUZlStXNooXL248+OCDRmxs7A2tt2bNGqN169ZObZMnTzbCwsKMvn37Gr///ruRmppqfPvtt0b58uWNL7744prPt2zZMqNixYrG6tWrjeTkZCM+Pt6YPXu2ERoaasTHxxuTJ0827rrrLuORRx4x/vzzTyMmJsbo3r27MW7cOMdzTJgwwahfv75j/925c6fRoEEDo2rVqo733TD+eu/37dt3Q9uZ19h/s09ezbBhw4wWLVoYe/fuNex2uxEZGWmMGDHCaNu2raOO+vXrG2+88YaRlpZmHDlyxKhWrZpjf83KyjJatGhhTJo0ybhw4YKRmppqrFy50ihfvryxf/9+x+ts3brVuOOOO4wFCxYY8fHxRkpKirFkyRIjJCTEOHHihGOft9lsRrdu3YxHH33UyMzMNAzDMObPn2+EhYUZLVu2NA4dOmSkpaUZW7duNWrWrOn0OVm0aJFRsWJFY+PGjUZqaqpx8OBBo0mTJsaoUaMcY/z9/R0/+/r6Gk2aNDHWrVtn2Gw2Y82aNUaxYsWc/p35t++ZYfz1+S9evLgRHBxsNG/e3Dh16pSjLy4uzihfvrwhyZBk1KxZ0zh37pyj/8svvzQ8PDyM0NBQIyQkxFi0aNEN1QIABR3BGwDyyZXBW5Kxe/dup/6GDRsae/fudTy+MnjbbDajfPnyTn8gG4Zh2O12o3z58saff/5pbN682QgODnYK7/fff7/x1FNPOa0zZ84cY/jw4YZh5A7eDz/8sNPY9u3bG//5z3+c2jp37mxs3brV8TgzM9MoWbKkcfbsWUfb34P3tWr4ex2GYRjDhw83PvjgA+PvxowZY7zzzjuO38+VoXf+/PlGiRIlnAJYYmKiERwcbOTk5OQK3haLxUhISHCMXbp0qWG1Wo34+HhH2/Lly42BAwfmquPy69WrV88Rlq4lPT3dWLVqlZGQkGBcunTJmDhxotGsWbPrrmcYf+0XV4ZZw/jr99WgQQMjOzvbqX3Pnj1GSEhIrvbLMjIyjJCQEOPIkSO5+s6fP+947lq1ahk5OTmOvmPHjhm1atUyDMMwzp07Z5QqVcqIiYlxWj86OtooWrSoy4P3zeyTV3P48GGjWrVqRmpqaq6+y9uf1/46d+5cx/66fPlyx5c5V1qzZo3RvXt3x+P69esbGzduvOrrTJ482Zg8ebLRunVr46mnnnJ6z+bPn2+EhIQYSUlJTuueOXPGKFWqlBEfH2/Y7XajTJkyxuHDh53GJCQkGOXKlTOOHTtmGIZz8JZkLFu2zGn8Qw895PQ5+rfv2Y4dO4zSpUsbW7duNZKTk40pU6YY9957r5GTk2NkZmYa9913nzFu3DgjLi7OiIyMNMaMGWMcOnTIMAzDyMnJMWrUqGFMnTrVSE5ONn788cc8txEACiOmmgOAG5QrV06NGzd2aqtWrZpiYmLyHH/kyBGdO3dO5cuXl8VicSyBgYGKjY11TF+tVauWihQp4rRu7969b/h1HnjgAafHpUqVUosWLZzaSpQo4TR9e9OmTQoLC1NISMhVt/ef1CBJP/74o0aPHu20rRaLRXPmzNGhQ4cc4+rXr++0XocOHeTv7+94HBgYKKvVqpSUlFyvUa9ePaeprKVKlVKdOnVUrFixq27rZfv27dMLL7ygL774wunCUVdjsVjUq1cvBQcHKygoSFOnTlVaWtp1z2HduHGjfH19c70vktSjRw95ejr/b7xRo0YKCAjQiRMn8ny+I0eOqFy5cnle3b1s2bKOn3v27CkPDw/H4ypVqjjer507d+r+++/PNT24fPnyatas2TW352bczD55NZs2bVKvXr3k5+eXq+/K7f/7/nrl9v/4449atWpVrn2zb9++Onz4sCQpPj5e586dU/v27a/5OjNmzFCdOnX04Ycf5novO3funOuiaBUrVtQ999yjvXv36siRIwoJCVG9evWcxgQHB6tr16768ccfc722h4eHevXq5dR2vc/iP/V///d/mjx5slq0aKGAgABNnjxZ0l+fmbVr18pqteqNN95wXNV82rRpGjBggOx2uw4fPqygoCBNnDhRAQEBatmypSZMmKCPPvrIZfUBgLsQvAHADYKCgnK1+fj4yG63X3WdRo0ayWaz5VoyMjIcF+0KDAy87mtd63WuDJ2S5O3treLFizu1eXp6Kisry/H4yquZX80/qeGyn376Kde22u12LVq0yDHm79v7T36vN7OtkhQVFaVevXrp008/Vc2aNa+5DddSpUoVnT17Vi+88ILTbcN+/fVXx5irndstKVddf/fwww87PW9qaqqys7Ovu56U+/dYpEgRx+/Qw8PD6RziG/XBBx841bNu3bobWu9m36e8uGL7pb/Ob8/rsxgZGel4ncvXBriWsLAwbdmyRRcuXMjVd73fcU5OzlW/9PHy8srzNlwWi0U+Pj5Obdf6LN7Me3by5MlcX+zUrVtXkZGROn78eK4vTfz9/RUcHKxffvnlmusCQGFH8AYAN/j70a3rqVOnjiIjIxUVFeXUnpKSomHDhjn+yPby8vpXr5XX+tc6opuVlaU1a9bowQcfvObz/tPtbd68ub755ptc7W+++abTxan+Xq+Z2yr9dVGtrl276vnnn1fXrl1v6HUyMjLUrl07paenO9rsdrv27dunGjVq6I033nC6dVjt2rUl/XVk1W6353nUVJJWrFihzMxMp7bdu3crNTVV1atX1//93/85Pa+/v7/uuusuRUdH53lf5ysvXHet32OzZs20devWXEdJz507d80raA8fPtypns6dO1917JVu5n26mpYtW2rlypVKTk7O1Xej23+1fXPdunVavHixpL+OypcuXVpr1qzJNe7K39sTTzyhwYMHq1WrVrl+n+vXr1dSUpJTW2RkpA4cOKBGjRo5AunJkyedxqSkpOjbb79Vy5Ytc732P/0c3sx7Vr58ef3yyy9Obb/88osqV66sKlWq6NixY059NptNv/32m8qWLZvnukeOHFHlypX/Ud0AUBARvAGggPL09HQEK4vFokmTJqlnz57at2+fMjIy9NNPP6lz584qWbLkP/6D2lV++OEHVa9eXeXLl/9Xz3PltkrSyy+/rNmzZ+uTTz5RUlKSLl68qMmTJ2v+/PmqVq3avy37pmRnZ6tv375q2bKl05Xmr8fHx0fBwcEaMWKEEhIS9Mcffyg8PFwNGzZU1apVr7retGnTrnnfbh8fH/Xu3VvHjx9XWlqa1q5dqz59+uidd9656v5gsVg0Y8YM9ejRQ1999ZWSk5OVkJCg9957T/fdd58uXbp03e0pW7ashg8frk6dOmnPnj2y2WzatWuXevfu7TSNWsr9vrpb48aN1aJFC7Vv31579+5VRkaGIiMjNXToUA0cOPCGnqNPnz66dOmSxowZo/PnzystLU1ffPGFBg8erLp16zrGzZo1S4MGDdL8+fMVHx+v1NRULVq0SA0bNtSpU6cc40aOHKlRo0apVatWOnfunKM9KChIPXr00OHDh2Wz2bRt2zZ16tRJzz//vIoVKyZfX1+9+uqr6tatm7Zu3Sqbzaaff/5ZXbt2VefOnVWrVq2b+h392/fsqaee0quvvqpt27YpJSVF06ZNk6+vr+69915169ZNBw8e1Jw5c5ScnKxz584pPDxcTZs2VUhIiBo3bqycnBxNmzZNKSkp2rZtm2bMmKHhw4ffdD0AUFAQvAGggGrVqpWqVaumXbt2SZKGDRumUaNGKTw8XEWLFtWDDz6oBx98UNOmTXNbjStWrLjuNPMb0bRpU02fPt0RaENDQ7Vx40atXr1a5cqVU40aNXTq1Clt2bLF6Rzu/DRy5Eht2LBBc+fOdZp+26ZNm+uuO2/ePGVnZ6tq1aqqXbu2/Pz89Nlnn111fHJyskqUKKFu3bpddcyjjz6qvn37qnv37ipWrJgmTpyoDz/88Lrvx+DBg/Xee+/p1VdfValSpRQWFqaDBw9q27ZtN3z7pilTpmjw4MF67LHHFBwcrDFjxujdd991Cp7SX+dnt2nTRsuXL7+h580PCxcuVLdu3fSf//xHRYsWVatWrVSqVCmtWrXqhtb39vbW+vXrlZ6errp166p06dKaN2+e1qxZ47T9HTt21IoVKzR//nyFhIQoNDRUq1ev1saNG3N94TJkyBC9+OKLatWqlWNadatWrTR+/HgNHjxYwcHBGjhwoEaPHq1x48Y51hs8eLBeeeUVPf30047blbVv315z5sy56d/Pv33P7r77bs2dO1dDhw5VaGiojhw5olWrVsnDw0MWi0Vr167V119/rTJlyqhx48YqXbq04/QRT09Pff3119q7d69CQkI0cuRILViw4Ka/RACAgsTDuJkTtQAAt73s7GzdcccdOnDggEJDQ91dDnDLWLBggfbv36/Zs2e7uxQAgItwxBsAcFMuXryoCRMmELoltWnTxuko+JXLleekw1y8DwCAgooj3gAAAAUIR7wB4NZD8AYAAAAAwERMNQcAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARP8fJQ+lf3iFZX0AAAAASUVORK5CYII=","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-2248 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-2248\n","不是      1490\n","是        878\n","不重要      563\n","问法错误      45\n","回答正确      24\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-2810 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-2810\n","不是      1342\n","是       1060\n","不重要      544\n","回答正确      31\n","问法错误      23\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** internlm/internlm2_5-7b-chat-1m_checkpoint-3372 **********\n","internlm/internlm2_5-7b-chat-1m_checkpoint-3372\n","不是      1338\n","是       1006\n","不重要      598\n","回答正确      30\n","问法错误      28\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["for col in df.columns[5:]:\n","    print(\"*\" * 10, col, \"*\" * 10)\n","    print(df[col].value_counts())\n","    plot_value_counts(df, col)"]},{"cell_type":"code","execution_count":15,"metadata":{},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n","\n","\n","def calc_metrics_for_col(df, col):\n","    y_true = df[\"label\"]\n","    y_pred = df[col]\n","\n","    accuracy = accuracy_score(y_true, y_pred)\n","    precision = precision_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","    recall = recall_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","    f1 = f1_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","\n","    return accuracy, float(precision), float(recall), float(f1)"]},{"cell_type":"code","execution_count":19,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["/var/folders/7x/56svhln929zdh2xhr3mwqg4r0000gn/T/ipykernel_34085/961288552.py:9: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n","  perf_df = pd.concat([perf_df, pd.DataFrame([new_model_metrics])], ignore_index=True)\n"]},{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>epoch</th>\n","      <th>model</th>\n","      <th>accuracy</th>\n","      <th>precision</th>\n","      <th>recall</th>\n","      <th>f1</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>internlm/internlm2_5-7b-chat-1m</td>\n","      <td>0.759667</td>\n","      <td>0.741854</td>\n","      <td>0.781014</td>\n","      <td>0.758887</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-562</td>\n","      <td>0.392000</td>\n","      <td>0.865731</td>\n","      <td>0.392000</td>\n","      <td>0.459125</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-1124</td>\n","      <td>0.611000</td>\n","      <td>0.807798</td>\n","      <td>0.611000</td>\n","      <td>0.674668</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-1686</td>\n","      <td>0.713667</td>\n","      <td>0.761735</td>\n","      <td>0.713667</td>\n","      <td>0.728502</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-2248</td>\n","      <td>0.653000</td>\n","      <td>0.749475</td>\n","      <td>0.653000</td>\n","      <td>0.685228</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>5</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-2810</td>\n","      <td>0.684667</td>\n","      <td>0.769066</td>\n","      <td>0.684667</td>\n","      <td>0.716450</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>6</td>\n","      <td>internlm/internlm2_5-7b-chat-1m_checkpoint-3372</td>\n","      <td>0.668333</td>\n","      <td>0.767219</td>\n","      <td>0.668333</td>\n","      <td>0.705321</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  epoch                                            model  accuracy  precision  \\\n","0     0                  internlm/internlm2_5-7b-chat-1m  0.759667   0.741854   \n","1     1   internlm/internlm2_5-7b-chat-1m_checkpoint-562  0.392000   0.865731   \n","2     2  internlm/internlm2_5-7b-chat-1m_checkpoint-1124  0.611000   0.807798   \n","3     3  internlm/internlm2_5-7b-chat-1m_checkpoint-1686  0.713667   0.761735   \n","4     4  internlm/internlm2_5-7b-chat-1m_checkpoint-2248  0.653000   0.749475   \n","5     5  internlm/internlm2_5-7b-chat-1m_checkpoint-2810  0.684667   0.769066   \n","6     6  internlm/internlm2_5-7b-chat-1m_checkpoint-3372  0.668333   0.767219   \n","\n","     recall        f1  \n","0  0.781014  0.758887  \n","1  0.392000  0.459125  \n","2  0.611000  0.674668  \n","3  0.713667  0.728502  \n","4  0.653000  0.685228  \n","5  0.684667  0.716450  \n","6  0.668333  0.705321  "]},"execution_count":19,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","perf_df = pd.DataFrame(columns=[\"epoch\", \"model\", \"accuracy\", \"precision\", \"recall\", \"f1\"])\n","for i, col in enumerate(df.columns[5:]):\n","    accuracy, precision, recall, f1 = calc_metrics_for_col(df, col)\n","    new_model_metrics = {\"epoch\": i, \"model\": col, \"accuracy\": accuracy, \"precision\": precision, \"recall\": recall, \"f1\": f1}\n","\n","    # Convert the dictionary to a DataFrame and concatenate it with the existing DataFrame\n","    perf_df = pd.concat([perf_df, pd.DataFrame([new_model_metrics])], ignore_index=True)\n","\n","perf_df"]},{"cell_type":"code","execution_count":24,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1200x500 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# plot metrics for each model\n","import matplotlib.pyplot as plt\n","\n","fig, ax = plt.subplots(1, 1, figsize=(12, 5))\n","\n","perf_df.plot(x=\"epoch\", y=[\"accuracy\", \"precision\", \"recall\", \"f1\"], kind=\"bar\", ax=ax)\n","\n","# add values on top of bars\n","for p in ax.patches:\n","    ax.annotate(\n","        f\"{p.get_height():.2f}\",\n","        (p.get_x() + p.get_width() / 2, p.get_height()),\n","        ha=\"center\",\n","        va=\"bottom\",\n","        fontsize=10,\n","    )\n","\n","# add title and labels\n","# ax.set_title(\"Metrics for different settings\")\n","# ax.set_ylabel(\"Value\")\n","ax.set_xlabel(\"Epoch (0: base model, 1-6: fine-tuned models)\")\n","# rotate x labels\n","plt.xticks(rotation=0)\n","\n","# set legend at the right to avoid overlapping with bars\n","plt.legend(loc=\"center left\", bbox_to_anchor=(1.0, 0.5))\n","# plt.tight_layout()\n","\n","plt.show()"]}],"metadata":{"accelerator":"GPU","application/vnd.databricks.v1+notebook":{"dashboards":[],"environmentMetadata":null,"language":"python","notebookMetadata":{"pythonIndentUnit":4},"notebookName":"07_MAC_+_Qwen2-7B-Instructi_Unsloth_train","widgets":{}},"colab":{"gpuType":"T4","provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.9"}},"nbformat":4,"nbformat_minor":0}