Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

Official implementation for BitVLA: 1-bit Vision-Language-Action Models for Robotics Manipulation

Running Microsoft's BitNet via Electron, React & Astro

Implementing the BitNet model in Rust

BitNet-Stack - Run a small BitNet model on local machine with one Docker command, and chat in browser.

Running Microsoft's BitNet inference framework via FastAPI, Uvicorn and Docker.

pure pytorch implementation of Microsoft's BitNet b1.58 2B4T

All the important tools for BITNET/HNET programs like relay chat, xyzzy, YWAKEUP, IUCVTRAP, CLRSCRN

Official implementation of BitMamba-2. A scalable 1.58-bit State Space Model (Mamba-2 + BitNet) trained from scratch on 150B tokens. Includes JAX training code and high-performance C++ inference engine.

BitNet: Learning-Based-Bit-Depth-Expansion

Ultra-lightweight C++ inference engine for BitMamba-2 (1.58-bit SSM). Runs 1B models on consumer CPUs at 50+ tok/s using <700MB RAM. No heavy dependencies.

Portable C inference engine for BitMamba-2 models

Run BitNet b1.58 ternary LLMs with WebGPU — in browsers and native apps

Rust bindings for bitnet.cpp based on llama-cpp-4

Peer-to-peer distributed AI inference using 1-bit quantized models. CPU-only, 70-82% energy savings, 103+ tokens/sec. Validated on Zen 4 & Zen 5 (+35% cross-gen improvement).

Ternlang is a ternary programming language (.tern) and a runtime for XAI, MoE-LLMs and autonomous agents, shipped with Agentic CLI and in house SDK/IDE.

An unofficial implementation of BitNet

Learning Path: RISC-V & Advanced Edge AI on SiFive FE310-G002 SoC | 32-bit RISC-V | 320 MHz | 16KB L1 Instruction Cache | 128Mbit (16MB) QSPI Flash | 4-stage pipeline

Pure Rust engine for BitNet LLMs — Conversion, Inference, Training and Research. With streaming and GPU/CPU support

Local, ternary-weight LLM inference on AMD Strix Halo. Rust above the kernels, HIP below, zero Python at runtime. https://discord.gg/EhQgmNePg