Comments (6)
https://github.com/datawhalechina/llm-universe
如果你对angchain不太熟悉,可以看下这个仓库
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第一个是部署api形式的llama3,第二个是部署langchian接入形式的llama3,第三个是部署webdemo对话,第四个是lora微调llama3.
如果你想要对话的话,可以尝试给第三个
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谢谢指点,请问第二个是部署langchian接入形式的llama3,这里的langchian就是可以接入很多大模型给自己选择用哪一个吗?
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详细内容,请看仓库文档
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大佬,在终端中运行以下命令,启动streamlit服务,并按照 autodl 的指示将端口映射到本地,然后在浏览器中打开链接 http://localhost:6006/ ,即可看到聊天界面。
这里怎么打开啊,我到这一步了
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多仔细看下教程文档
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Related Issues (20)
- 【非Issues!讨论帖】通过lora微调的qianwen和直接使用system来预设的区别貌似不是很大 HOT 3
- ChatGLM3-6B微调后成哑巴了(字面意思) HOT 4
- 我想我可不可提交给PR支持一下BlueLM我们的蓝心大模型 HOT 1
- 关于模型的api部署,能否推出高性能的异步版本、例如使用vllm、或者fastchat等工具 HOT 1
- 请问chatglm模型Lora微调完成之后,如何加载新模型? HOT 8
- Qwen-1.5-4B LLM推理bug HOT 3
- chatglm3-6b fastapi调用 HOT 1
- 建议按照顺序撰写README部分教程 HOT 1
- 与FastChat的区别
- 多卡报错,Qwen1.5-7B-Chat FastApi 部署调用 HOT 3
- 请问ChatGLM3微调中的数据集huanhuan的在哪获取? HOT 3
- qwen-vl
- deepseek lora HOT 2
- LLaMA3-8B-Instruct+lora使用A800(80GB显存)微调长度8192 HOT 2
- peft训练完成,参考的是04-Qwen-7B-Chat Lora 微调.ipynb,但是重新载入模型时,提示peft版本问题,用的是model = AutoModelForCausalLM.from_pretrained("../output/Qwen/checkpoint-1300/", trust_remote_code=True).eval(),提示的错误时ValueError: The version of PEFT you are using is not compatible, please use a version that is greater than 0.5.0 HOT 2
- 想问下在这个项目下的lora微调和Chatglm3官方微调的demo的数据格式怎么不一样呀 HOT 1
- 报错asyncio.run() cannot be called from a running event loop,辛苦大佬们看看 HOT 6
- InternLM2 缺少包 HOT 2
- Building wheel for flash-attn (setup.py) ... - 卡住了。 HOT 4
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