Build high-performance AI models with modular building blocks
Appears on
Quick read
Latest capture 2026-08-15 03:06
0 paths
Agent instructions and tool configuration found in this repository.
No config files detected.
6 observed captures since 2026-05-27. Observed captures are shown by default.
Stars from first capture +6
Observed captures only
All tracked data
Observed snapshots
Observed snapshots
Nearest indexed repositories by embedding similarity.
Any model. Any hardware. Zero compromise. Built with @ziglang / @openxla / MLIR / @bazelbuild
A deep learning framework built on an autograd engine with high level abstractions and low level control.
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
Ongoing research training transformer models at scale
Complete API layer for private AI applications on local models: RAG, skills, tools, MCP, text-to-sql, and more. Works with any OpenAI-compatible inference server.
Fast, small, secure, local-first personal AI assistant infrastructure: one Rust binary for tools, memory, channels, providers, and sandboxed autonomy.
