ローカルLLM
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An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
★ 39.6k スターApache-2.0
ガイドを見る →BitNetは、microsoftが公開しているオープンソースのローカルLLMプロジェクトです（GitHub: microsoft/BitNet）。GitHubスターは41,232、フォークは3,837で、MITライセンスの下で公開されています。GitHubでの最終更新は2026年7月27日です。
BitNet — Microsoft's official inference framework for 1-bit large language models, running fast on ordinary CPUs, MIT
Clone with submodules, create the recommended conda environment, and install the Python requirements.
Fetch the official BitNet b1.58 2B GGUF weights from Hugging Face into a local models directory.
Point setup_env.py at the downloaded model with the i2_s quantisation and run inference locally.
Ternarised weights (-1, 0, 1) shrink the model so far that capable LLMs run fast on ordinary CPUs instead of needing a GPU.
The reference implementation for BitNet models, with the technical report (arXiv 2502.11880) behind the 1-bit approach.
A GPU kernel path exists alongside the CPU-first design for machines that do have a graphics card.
The same project line now includes 1-bit embeddings and a 1-bit speech-recognition engine (VibeASR.cpp), not just chat models.
The README build route: recursive clone, conda environment, requirements.
git clone --recursive https://github.com/microsoft/BitNet.git
conda create -n bitnet-cpp python=3.10
conda activate bitnet-cpp
pip install -r requirements.txtThe official 2B model weights from Hugging Face.
huggingface-cli download microsoft/BitNet-b1.58-2B-4T-gguf --local-dir models/BitNet-b1.58-2B-4TPrepare the model directory for inference with the i2_s quantisation.
python setup_env.py -md models/BitNet-b1.58-2B-4T -q i2_sMicrosoft, as the official inference framework for its 1-bit LLM research.
Yes — MIT licensed, and the model weights are distributed on Hugging Face under their own terms.
Model weights are ternarised to just three values (-1, 0, 1) instead of 16-bit floats, which slashes memory and lets CPUs run the model fast.
No — CPU inference is the point of the framework, though a GPU kernel path exists for machines that have one.
Clone recursively, set up the conda environment, download the BitNet-b1.58-2B-4T GGUF weights, and run setup_env.py against them.
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
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LibreAIカタログに掲載されたローカルLLMプロジェクトの中で最もスターの多いもの — BitNetが合わなかった場合に検討したい、現実的な候補リストです。
The simplest way to run open language models on your own machine.
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LLM inference in C/C++
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カタログの中でBitNetとスター数が近いローカルLLMプロジェクト — 前後の棚もそのまま見て回れます。
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An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
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