Qwen学习笔记2：Qwen模型基于ReAct原理实现function calling

最新推荐文章于 2025-05-06 14:38:22 发布

金桃不烦恼

最新推荐文章于 2025-05-06 14:38:22 发布

阅读量5.1k

点赞数 34

分类专栏：深度学习-大模型文章标签：学习笔记 chatgpt

本文链接：https://blog.youkuaiyun.com/weixin_42118737/article/details/138917737

版权

前言

这也是一篇笔记，再探索一下Qwen模型的function calling功能。

Qwen1.8B模型能够进行function calling功能吗？

我们使用之前的reason_prompt模板进行测试：

PROMPT_REACT = """
Use the following format:

Question: the input question you must answer
Thought: you should always think about what to do

Begin!

Question:{query}"""

Use the following format:

Question: the input question you must answer
Thought: you should always think about what to do

Begin!

Question:请帮我查一下：我们的大模型技术实战课程目前一共上线了多少节？

1.8B模型无法进入到思维链模式

7B模型下测试，确实还有区别的，开始进行思考了！

在上一篇笔记的基础上再增加一个功能，进一步事件模型的函数调用功能。

再次注明该文章的代码来源于：

【太牛了】Qwen结合ReAct，几分钟就能构建一个AI Agent，保姆级实操讲解，理论与实践相结合，讲述ReAct是如何作用于Qwen模型的_哔哩哔哩_bilibili

大家可以自行去学习，这里我只是记录一下学习的过程。

主要代码

导入相关库

from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers.generation import GenerationConfig

D:\ProgramData\anaconda3\envs\qwen\Lib\site-packages\tqdm\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
  from .autonotebook import tqdm as notebook_tqdm

加载模型

# model_path = './model/qwen/Qwen-1_8B-Chat'
model_path = './model/qwen/Qwen-7B-Chat'
tokenizer=AutoTokenizer.from_pretrained(model_path,trust_remote_code=True)
model=AutoModelForCausalLM.from_pretrained(model_path,device_map="auto",trust_remote_code=True)

注意我这里修改为本地的模型路径，按照大家安装的实际位置为准。

The model is automatically converting to bf16 for faster inference. If you want to disable the automatic precision, please manually add bf16/fp16/fp32=True to "AutoModelForCausalLM.from_pretrained".
Try importing flash-attention for faster inference...
Warning: import flash_attn rotary fail, please install FlashAttention rotary to get higher efficiency https://github.com/Dao-AILab/flash-attention/tree/main/csrc/rotary
Warning: import flash_attn rms_norm fail, please install FlashAttention layer_norm to get higher efficiency flash-attention/csrc/layer_norm at main · Dao-AILab/flash-attention · GitHub
Loading checkpoint shards: 100%|████████████████████