use Qwen/Qwen2-0.5B-Instruct

Signed-off-by: Zhang Jun <[email protected]>

app.py

@@ -1,8 +1,8 @@
 import gradio as gr
 from paddlenlp.transformers import AutoTokenizer, AutoModelForCausalLM
 
-tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2-0.5B")
-model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-0.5B", dtype="float32")
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2-0.5B-Instruct")
+model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-0.5B-Instruct", dtype="float32")
 
 
 def inference(input_text):
@@ -20,7 +20,7 @@ title = 'PaddlePaddle Meets LLM'
 description = '''
 - The underlying execution framework is based on [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) and [PaddleNLP](https://github.com/PaddlePaddle/PaddleNLP).
 - PaddleNLP supports a wide range of open-source LLMs. Check out the [full model list](https://github.com/PaddlePaddle/PaddleNLP?tab=readme-ov-file#%E6%A8%A1%E5%9E%8B%E6%94%AF%E6%8C%81).
-- We chose QWEN2-0.5B as the model for this use case due to limited computational resources.
+- We chose QWEN2-0.5B-Instruct as the model for this use case due to limited computational resources.
 - [ERNIE 4.5](https://yiyan.baidu.com/) was trained with PaddlePaddle, [give it a try](https://huggingface.co/spaces/PaddlePaddle/ernie_demo)!
 '''