ai-agent

Run LLMs Locally with awesome-local-llm

Name: Run LLMs Locally with awesome-local-llm
Author: rafska

Get local LLM resources for self-hosted AI. For founders, with 2.4k+ GitHub stars.

2,419 stars299 forksQuality 8/10Updated 7/22/2026100% free · open source

What it does

Awesome-local-llm provides a curated list of resources and tools to help founders self-host and run large language models (LLMs) locally.

Install / run

Clone the repository using the command `git clone https://github.com/rafska/awesome-local-llm.git`

When to use it

•When you need to deploy AI models on-premises due to data privacy concerns
•When you want to reduce cloud costs by running AI workloads locally
•When you need more control over the AI infrastructure and model updates

Quick start

1Browse the README.md file to understand the list of curated resources and tools
2Explore the `platforms` section for local LLM deployment options, such as Docker or Kubernetes
3Check the `tools` section for libraries and frameworks to build and train LLMs, like Hugging Face Transformers
4Visit the linked GitHub repositories for each tool or platform to learn more about their usage and configuration
5Search for tutorials or guides in the `resources` section to get started with self-hosting LLMs

Ready-to-paste prompt

To get started with a specific LLM platform, for example, Docker, paste the command `docker run -it --rm rafsk/llm-local` to run a local LLM instance

Heads up: Make sure you have Git installed on your system and configured properly to clone the repository, as some resources may require Git for deployment or setup

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