https://github.com/whatishedoing/localllm
Set up, augment and experiment with Large Language Models locally.
https://github.com/whatishedoing/localllm
Last synced: about 1 year ago
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Set up, augment and experiment with Large Language Models locally.
- Host: GitHub
- URL: https://github.com/whatishedoing/localllm
- Owner: WhatIsHeDoing
- License: unlicense
- Created: 2024-02-24T21:59:42.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-03-15T12:36:12.000Z (over 2 years ago)
- Last Synced: 2025-02-16T07:54:31.766Z (over 1 year ago)
- Language: Python
- Size: 48.8 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Local LLM
## 👋🏻 Introduction
This repository is used to set up, augment and experiment with Large Language Models (LLMs) locally.
## 👟 Getting Started
1. First, clone an LLM such as [Llama] using `make clone_llm`.
Adjust the LLM size in the [Makefile] based on the amount of memory available on your computer.
1. Next, install Python dependencies with `make install`.
1. Parse the test data used to augment the LLM by running `make parse`.
1. Run the chatbot command line app with `make run` to see it in action with the test data.```
If any of the previous steps fail, try installing the dependencies for your Operating System
using an appropriate script in the `config` directory, such as `.\config\config_windows.ps1`.
## 🔧 Customising
Use an `.env` file to customise some of the configuration of the scripts, particularly to point to your data.
Look at the instructions in [`.env.example`][env] for details.
## 🆘 Contributing
All contributions are greatly appreciated! Please add the [pre-commit] hooks
using `make pre_commit_setup` to run quality checks on the codebase before submitting a Pull Request.
These can be run ad hoc with `make lint`.
## 🔗 References
- [Scott Harden]: Using Llama 2 to Answer Questions About Local Documents
[env]: ./.env.example
[Llama]: https://llama.meta.com/
[Makefile]: ./Makefile
[pre-commit]: https://pre-commit.com/
[Scott Harden]: https://swharden.com/blog/2023-07-30-ai-document-qa/