Kh4L/deepseek-harness
DeepSeek Harness: Everything is a Plugin.
DeepSeek Harness: Everything is a Plugin.
AI agent toolkit: coding agent CLI, unified LLM API, TUI & web UI libraries, Slack bot, vLLM pods
RelBench: Relational Deep Learning Benchmark
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
Scalable toolkit for efficient model reinforcement
Common recipes to run vLLM
A high-throughput and memory-efficient inference and serving engine for LLMs
Build RL environments for LLM training
FlashInfer: Kernel Library for LLM Serving
Run OpenClaw more securely inside NVIDIA OpenShell with managed inference
OpenShell is the safe, private runtime for autonomous AI agents.
The fastest repo in history to surpass 50K stars ⭐, reaching the milestone in just 2 hours after publication. Better Harness Tools that make real things done. Now writing in Rust using oh-my-codex.
AI agents running research on single-GPU nanochat training automatically
SGLang is a fast serving framework for large language models and vision language models.
Graph-JEPA: GNN+LLM with JEPA pretraining
Fast and memory-efficient exact attention
PyTorch media decoding and encoding
Knowledge Graph Generation from Any Text
A library for efficient similarity search and clustering of dense vectors.
Low-Level Graph Neural Network Operators for PyG
👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)
Fully open reproduction of DeepSeek-R1
Graph Neural Network Library for PyTorch
Graph Foundation Model for Retrieval Augmented Generation
Custom C++ vanilla RNN implementation with Eigen
Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation
Open standard for machine learning interoperability
NLP made easy
Code and documentation to train Stanford's Alpaca models, and generate the data.
Playing around with stable diffusion. Generated images are reproducible because I save the metadata and latent information. You can generate and then later interpolate between the images of your choice.