plz work

app.py

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+import gradio as gr
+from transformers import T5ForConditionalGeneration, AutoTokenizer, TrainingArguments
+
+tokenizer = AutoTokenizer.from_pretrained('evanthebouncy/cad-llm')
+model = T5ForConditionalGeneration.from_pretrained('evanthebouncy/cad-llm')
+
+temp = 1.0
+
+def generate_samples_with_temp(txt_n):
+    txt, n = txt_n.split('|')
+    n_samples = int(n)
+    to_tokenizer = [txt for i in range(n_samples)]
+    outputs = model.generate(tokenizer(to_tokenizer, return_tensors='pt', padding=True).input_ids, do_sample=True, max_length=128, temperature = temp)
+    results = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    return '\n'.join(results)
+
+
+iface = gr.Interface(fn=generate_samples_with_temp, inputs="text", outputs="text")
+iface.launch()

requirements.txt

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+certifi==2022.9.14
+charset-normalizer==2.1.1
+filelock==3.8.0
+huggingface-hub==0.9.1
+idna==3.4
+numpy==1.23.3
+packaging==21.3
+pyparsing==3.0.9
+PyYAML==6.0
+regex==2022.9.13
+requests==2.28.1
+tokenizers==0.12.1
+torch==1.12.1
+tqdm==4.64.1
+transformers==4.22.1
+typing_extensions==4.3.0
+urllib3==1.26.12
+