local-llm is a development framework that enables developers to run large language models locally within Google Cloud Workstations or standard environments without requiring GPU hardware. It focuses on making generative AI development more accessible by leveraging quantized models and CPU-based execution, eliminating the dependency on expensive GPU infrastructure. The repository includes tools, Docker configurations, and command-line utilities that simplify the process of downloading, running, and interacting with language models directly on local or cloud-based workstations. This approach improves data privacy and control, as all inference can be performed locally without sending sensitive information to external APIs. It also integrates seamlessly with Google Cloud services, allowing developers to build and test AI-powered applications within the broader cloud ecosystem.

Features

  • Run large language models locally without GPUs
  • Support for quantized models from external repositories
  • Integration with Google Cloud Workstations environments
  • Command-line tools for model execution and interaction
  • Docker-based setup for reproducible environments
  • Improved data privacy through local inference

Project Samples

Project Activity

See All Activity >

License

Apache License V2.0

Follow local-llm

local-llm Web Site

Other Useful Business Software
Our Free Plans just got better! | Auth0 Icon
Our Free Plans just got better! | Auth0

With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
Try free now
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of local-llm!

Additional Project Details

Programming Language

Python

Related Categories

Python Large Language Models (LLM)

Registered

2026-03-17