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README.md

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-# Chat with Meta's LLaMA models at home made easy
-
-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.
-
-This repo is heavily based on Meta's original repo: https://github.com/facebookresearch/llama
-
-And on Venuatu's repo: https://github.com/venuatu/llama
-
-### Examples of chats here
-
-https://github.com/facebookresearch/llama/issues/162
-
-### System requirements
-- Modern enough CPU
-- NVIDIA graphics card
-- 64 or better 128 Gb of RAM (192 or 256 would be perfect)
-
-One may run with 32 Gb of RAM, but inference will be slow (with the speed of your swap file reading)
-
-I am running this on 12700k/128 Gb RAM/NVIDIA 3070ti 8Gb/fast huge nvme and getting one token from 30B model in a few seconds.
-
-For example, 30B model uses around 70 Gb of RAM.
-
-If you do not have powerful videocard, you may use another repo for cpu-only inference: https://github.com/randaller/llama-cpu
-
-### Conda Environment Setup Example for Windows 10+
-Download and install Anaconda Python https://www.anaconda.com and run Anaconda Prompt
-```
-conda create -n llama python=3.10
-conda activate llama
-conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia
-```
-
-### Setup
-In a conda env with pytorch / cuda available, run
-```
-pip install -r requirements.txt
-```
-Then in this repository
-```
-pip install -e .
-```
-
-### Download tokenizer and models
-magnet:?xt=urn:btih:ZXXDAUWYLRUXXBHUYEMS6Q5CE5WA3LVA&dn=LLaMA
-
-or
-
-magnet:xt=urn:btih:b8287ebfa04f879b048d4d4404108cf3e8014352&dn=LLaMA&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce
-
-### Prepare model
-
-First, you need to unshard model checkpoints to a single file. Let's do this for 30B model.
-
-```
-python merge-weights.py --input_dir D:\Downloads\LLaMA --model_size 30B
-```
-
-In this example, D:\Downloads\LLaMA is a root folder of downloaded torrent with weights.
-
-This will create merged.pth file in the root folder of this repo.
-
-Place this file and corresponding (torrentroot)/30B/params.json of model into [/model] folder.
-
-So you should end up with two files in [/model] folder: merged.pth and params.json.
-
-Place (torrentroot)/tokenizer.model file to the [/tokenizer] folder of this repo. Now you are ready to go.
-
-### Run the chat
-
-```
-python example-chat.py ./model ./tokenizer/tokenizer.model
-```
-
-### Enable multi-line answers
-
-If you wish to stop generation not by "\n" sign, but by another signature, like "User:" (which is also good idea), or any other, make the following modification in the llama/generation.py:
-
-![image](https://user-images.githubusercontent.com/22396871/224122767-227deda4-a718-4774-a7f9-786c07d379cf.png)
-
--5 means to remove last 5 chars from resulting context, which is length of your stop signature, "User:" in this example.