Explore projects

https://github.com/Portkey-AI/portkey-python-sdk Build reliable, secure, and production-ready AI apps easily.

🔧🔗github hf diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

🕸️🔗huggingface.co/docs/diffusers

🔧🔗https://github.com/HumanSignal/label-studio-ml-backend

Configs and boilerplates for Label Studio's Machine Learning backend

🐚 OpenDevin: Code Less, Make More https://github.com/OpenDevin/OpenDevin

https://github.com/janhq/jan Jan is an open source alternative to ChatGPT that runs 100% offline on your computer. Multiple engine support (llama.cpp, TensorRT-LLM) 🔗 https://jan.ai

https://github.com/janhq/cortex.cpp

🔧🔗https://github.com/rsyncOSX/RsyncUI

A SwiftUI based macOS GUI for rsync.

🔧🔗https://github.com/AvitalTamir/cyphernetes

A Kubernetes Query Language

https://github.com/awesome-selfhosted/awesome-selfhosted-data machine-readable data for https://awesome-selfhosted.net

🔧🔗https://github.com/modelscope/ms-swift

SWIFT (Scalable lightWeight Infrastructure for Fine-Tuning) Use PEFT or Full-parameter to finetune 400+ LLMs or 100+ MLLMs.

https://github.com/anyproto/anytype-swift Official Anytype client for iOS

🔧🔗https://github.com/huggingface/agents

🤗 Agents: the simplest building blocks to build and run LLM agents.

🔧🔗https://github.com/modelscope/evalscope A streamlined and customizable framework for efficient large model evaluation and performance benchmarking

https://github.com/VictoriaMetrics/VictoriaMetrics VictoriaMetrics: fast, cost-effective monitoring solution and time series database

🔧🔗https://github.com/bytedance/vArmor vArmor is a cloud native container sandbox system based on AppArmor/BPF/Seccomp. It also includes multiple built-in protection rules that are ready to use out of the box.

🔧🔗https://github.com/huggingface/lerobot

🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning

🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 11 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴 https://github.com/decodingml/llm-twin-course