| | from transformers import AutoTokenizer, AutoModelForCausalLM |
| | import torch |
| | import gradio as gr |
| |
|
| | model_name = "tosei0000/chatbot" |
| |
|
| | tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) |
| | model = AutoModelForCausalLM.from_pretrained( |
| | model_name, |
| | torch_dtype=torch.bfloat16, |
| | trust_remote_code=True |
| | ) |
| |
|
| | device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
| | model = model.to(device) |
| |
|
| | tokenizer.pad_token_id = tokenizer.eos_token_id |
| | model.config.pad_token_id = tokenizer.eos_token_id |
| |
|
| | def chat(user_input, history): |
| | prompt = "".join( |
| | f"User: {u}\nAssistant: {a}\n" for u, a in history |
| | ) + f"User: {user_input}\nAssistant:" |
| | inputs = tokenizer(prompt, return_tensors="pt").to(device) |
| | output = model.generate( |
| | **inputs, |
| | max_new_tokens=256, |
| | do_sample=True, |
| | temperature=0.7, |
| | top_p=0.9, |
| | pad_token_id=tokenizer.pad_token_id, |
| | eos_token_id=tokenizer.eos_token_id |
| | ) |
| | text = tokenizer.decode(output[0], skip_special_tokens=True) |
| | reply = text[len(prompt):].strip().split("\n")[0] |
| | history.append((user_input, reply)) |
| | return history, history |
| |
|
| | with gr.Blocks(title="Qwen2 Chatbot") as demo: |
| | gr.Markdown("## 🤖 杜靖 聊天机器人") |
| | chatbot = gr.Chatbot() |
| | msg = gr.Textbox(label="输入你的问题") |
| | clear = gr.Button("清除对话") |
| | state = gr.State([]) |
| |
|
| | msg.submit(chat, [msg, state], [chatbot, state]) |
| | clear.click(lambda: ([], []), None, [chatbot, state]) |
| |
|
| | if __name__ == "__main__": |
| | demo.launch() |
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