Stars
A unified library of SOTA model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks …
Fast, small, and fully autonomous AI personal assistant infrastructure, ANY OS, ANY PLATFORM — deploy anywhere, swap anything 🦀
AI agent toolkit: coding agent CLI, unified LLM API, TUI & web UI libraries, Slack bot, vLLM pods
IronClaw is OpenClaw inspired implementation in Rust focused on privacy and security
With this tool you can create custom TTS dataset from video or audio.
REAP: Router-weighted Expert Activation Pruning for SMoE compression
NVIDIA Linux open GPU with P2P support
NVIDIA Linux open GPU with P2P support
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Easily fine-tune, evaluate and deploy gpt-oss, Qwen3, DeepSeek-R1, or any open source LLM / VLM!
Beads - A memory upgrade for your coding agent
Semi-Structured Agentic Framework. Workflows build themselves as agents discover what needs to be done, not what you predicted upfront.
Dataset containing IR, visible and audio data to be used to train drone detection systems.
Supercharge Your LLM with the Fastest KV Cache Layer
Official implementation of "Depth Any Panoramas: A Foundation Model for Panoramic Depth Estimation".
Generate High-Quality Synthetics, Train, Measure, and Evaluate in a Single Pipeline
GUI for a Vocal Remover that uses Deep Neural Networks.
Utility for mass-downloading LRC synced lyrics for your offline music library.
Kaleido: Open-sourced multi-subject reference video generation model, enabling controllable, high-fidelity video synthesis from multiple image references.
[ICLR 2026] RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning.
The dataset for drone based detection and tracking is released, including both image/video, and annotations.
[NeurIPS 2024] Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation