app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

from huggingface_hub import login
login(token="你的Token")  # 添加在模型加载前

model = AutoModelForCausalLM.from_pretrained(
    "Qwen/Qwen2.5-7B-Instruct-AWQ",
    device_map="auto",
    use_auth_token=True,  # 启用认证
    resume_download=True,  # 断点续传
    local_files_only=False
)

# 定义生成函数
def generate_response(message, history):
    # 格式化对话历史
    messages = [{"role": "user", "content": message}]
    text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
    inputs = tokenizer(text, return_tensors="pt").to(model.device)
    
    # 生成回复
    outputs = model.generate(
        **inputs,
        max_new_tokens=512,
        temperature=0.7
    )
    response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
    return response

# 启动Gradio界面
gr.ChatInterface(
    fn=generate_response,
    title="Qwen2.5-7B大模型在线演示",
    description="输入问题后按回车开始对话"
).launch()