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49 lines
1.6 KiB
Markdown
49 lines
1.6 KiB
Markdown
# Chat with Meta's LLaMA models at home made easy
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This repository is a chat example with [LLaMA](https://ai.facebook.com/blog/large-language-model-llama-meta-ai/) ([arXiv](https://arxiv.org/abs/2302.13971v1)) models running on a typical home PC. You will just need a NVIDIA videocard and some RAM to chat with model.
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### Conda Environment Setup Example for Windows 10+
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Download and install Anaconda Python https://www.anaconda.com and run Anaconda Prompt
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```
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conda create -n llama python=3.10
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conda activate llama
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conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia
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```
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### Setup
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In a conda env with pytorch / cuda available, run
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```
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pip install -r requirements.txt
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```
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Then in this repository
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```
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pip install -e .
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```
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### Download tokenizer and models
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magnet:?xt=urn:btih:ZXXDAUWYLRUXXBHUYEMS6Q5CE5WA3LVA&dn=LLaMA
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or
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magnet:xt=urn:btih:b8287ebfa04f879b048d4d4404108cf3e8014352&dn=LLaMA&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce
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### Prepare model
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First, you need to unshard model checkpoints to a single file. Let's do this for 30B model.
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```
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python merge_weights.py --input_dir D:\Downloads\LLaMA --model_size 30B
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```
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In this example, D:\Downloads\LLaMA is a root folder of downloaded torrent with weights.
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This will create merged.pth file in the root folder of this repo.
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Place this file and corresponding (torrentroot)/30B/params.json of model into [/model] folder.
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Place (torrentroot)/tokenizer.model file to the [/tokenizer] folder of this repo. Now you are ready to go.
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```
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python example-chat.py ./model ./tokenizer/tokenizer.model
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```
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