如何修改Python代码以访问通过Ollama部署的Llama 3.3模型
问题描述
已通过以下命令在远程GPU上使用Ollama安装了Llama 3.3:
curl -fsSL https://ollama.com/install.sh | sh ollama run llama3.3
现在想要运行以下调用Llama 3.3的Python代码,请问需要对代码做哪些修改?
import transformers import torch model_id = "meta-llama/Llama-3.3-70B-Instruct" pipeline = transformers.pipeline( "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto", ) messages = [ {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"}, {"role": "user", "content": "Who are you?"}, ] outputs = pipeline( messages, max_new_tokens=256, ) print(outputs[0]["generated_text"][-1])
修改方案
原代码基于Hugging Face transformers 库直接加载模型,而你通过Ollama部署的Llama 3.3是通过API提供服务的,因此需要将逻辑改为调用Ollama API,具体修改如下:
1. 替换依赖库
移除transformers和torch,改用Ollama官方Python库(或直接用requests调用API)。若使用官方库,先执行安装命令:
pip install ollama
2. 调整代码逻辑
方式一:使用Ollama官方Python库
修改后的代码示例:
import ollama # 若远程GPU的Ollama服务非本地访问,需设置服务地址 # ollama.set_base_url("http://远程GPU的IP:11434") messages = [ {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"}, {"role": "user", "content": "Who are you?"}, ] # 调用Ollama的对话接口,指定模型为llama3.3 response = ollama.chat( model="llama3.3", messages=messages, options={"max_tokens": 256} ) # 打印生成的回复内容 print(response['message']['content'])
方式二:直接用requests调用API
若不想安装Ollama的Python库,可直接通过HTTP请求调用:
import requests # 远程GPU的Ollama服务地址,默认端口为11434 url = "http://远程GPU的IP:11434/api/chat" messages = [ {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"}, {"role": "user", "content": "Who are you?"}, ] payload = { "model": "llama3.3", "messages": messages, "options": {"max_tokens": 256}, "stream": False # 关闭流式输出,直接获取完整结果 } response = requests.post(url, json=payload) result = response.json() print(result['message']['content'])
3. 关键修改点说明
- 不再需要指定Hugging Face的模型ID,直接使用Ollama中部署的模型名称
llama3.3 - 调用逻辑从本地加载模型改为调用Ollama的API接口,远程访问时需指定正确的服务地址
- 输出结果的解析方式改为提取Ollama API返回的
message.content字段
内容的提问来源于stack exchange,提问作者pkjpk
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