Create app.py

app.py

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+import torch
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+
+path = "jianghc/medical_chatbot"
+device = "cuda" if torch.cuda.is_available() else "cpu"
+tokenizer = GPT2Tokenizer.from_pretrained(path)
+model = GPT2LMHeadModel.from_pretrained(path).to(device)
+
+prompt_input = (
+    "The conversation between human and AI assistant.\n"
+    "[|Human|] {input}\n"
+    "[|AI|]"
+)
+sentence = prompt_input.format_map({'input': "what is parkinson's disease?"})
+inputs = tokenizer(sentence, return_tensors="pt").to(device)
+
+with torch.no_grad():
+    beam_output = model.generate(**inputs,
+                                min_new_tokens=1, 
+                                max_length=512,
+                                num_beams=3,
+                                repetition_penalty=1.2,
+                                early_stopping=True,
+                                eos_token_id=198 
+                                )
+    print(tokenizer.decode(beam_output[0], skip_special_tokens=True))