bitnet-mlx.rs
What it is
A Rust implementation of BitNet neural networks optimized for Apple Silicon, featuring 1.58-bit quantization and GPU acceleration via Metal and MLX. It provides a CLI for text generation and an infrastructure for training custom models.
The problem it solves
Standard LLMs require high memory and computational resources, making them difficult to run or train on consumer hardware like Apple Silicon.
What you could use it for
- Running 1.58-bit quantized LLMs on Apple Silicon devices
- Training custom BitNet models with low memory footprint
- Deploying efficient inference pipelines using Rust
Read the source ↗Back to the library →
Summary written by an AI model from the source; check the source before you rely on it.