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Gpt4all: 一个在基于LLaMa的约800k GPT-3.5-Turbo Generations上训练的聊天机器人

基于 LLaMa 的 ~800k GPT-3.5-Turbo Generations 训练助手式大型语言模型的演示、数据和代码

Try it yourself

Download the CPU quantized gpt4all model checkpoint: gpt4all-lora-quantized.bin

gpt4all-lora-quantized.bin 这个文件有 4.2GB ,存放在 amazonaws 上,下不了自行科学

Clone this repository down and place the quantized model in the chat directory and start chatting by running:

cd chat;./gpt4all-lora-quantized-OSX-m1 on M1 Mac/OSX
cd chat;./gpt4all-lora-quantized-linux-x86 on Windows/Linux

To compile for custom hardware, see our fork of the Alpaca C++ repo.

Note: the full model on GPU (16GB of RAM required) performs much better in our qualitative evaluations.

三步曲

  1. 下载 gpt4all-lora-quantized.bin 下列网址都可尝试
  2. 下载 gpt4all-lora-quantized-linux-x86 或 其它平台程序
  3. 把上面两个文件放在一个文件夹里,运行
-rw-r--r-- 1 root root 4212732137 Mar 29 11:48 gpt4all-lora-quantized.bin
-rwxr-xr-x 1 root root     410392 Mar 29 11:49 gpt4all-lora-quantized-linux-x86

例如我让它用python写一个一元一次方程:

效果还不错(不管它写得对不对,总算是写出来了),主要是依赖训练语料!

像官方 readme 里的示例问题,回答效果很好

https://chat.openai.com/ 上提问的结果,对比一下:

问题: How to write a linear equation with one unknown in python?

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