Deep Learning Library
1.9k 2026-04-18
kyegomez/BitNet
A PyTorch implementation of BitNet, enabling highly efficient 1-bit transformers for large language models.
Core Features
Implements BitLinear, BitAttention (BitMGQA), and BitFeedForward modules.
Optimizes transformer architectures for 1-bit quantization.
Facilitates easy integration by replacing standard linear layers.
Enhances decoding speed and context handling with Multi-Grouped Query Attention.
Supports training and finetuning of 1-bit LLMs from scratch.
Quick Start
pip3 install bitnetDetailed Introduction
BitNet is a PyTorch-based open-source project that implements the "BitNet: Scaling 1-bit Transformers for Large Language Models" paper. Its core innovation lies in quantizing transformer components, particularly linear layers, to 1-bit precision. This significantly reduces memory footprint and computational costs, making large language models more accessible and efficient. The project offers modular components like `BitLinear` and `BitMGQA` for easy integration into existing or new LLM architectures, aiming to push the boundaries of efficient AI.