| import gradio as gr |
| from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM |
| import torch |
|
|
| model_dir = "./" |
| tokenizer = AutoTokenizer.from_pretrained(model_dir) |
| model = AutoModelForCausalLM.from_pretrained(model_dir) |
|
|
| generator = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if torch.cuda.is_available() else -1) |
|
|
| def generate_answer(prompt): |
| output = generator(prompt, max_length=100, do_sample=True, top_p=0.95, temperature=0.7) |
| return output[0]['generated_text'] |
|
|
| gr.Interface(fn=generate_answer, inputs="text", outputs="text", title="Medical Chatbot").launch() |
|
|
