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bitnet.cpp is the official inference framework for 1-bit LLMs (e.g., BitNet b1.58). It offers a suite of optimized kernels, that support fast and lossless inference of 1.58-bit models on CPU (with NPU and GPU support coming next).
Key Features of BitNet.cpp. BitNet.cpp comes with a treasure trove 🪙 of features designed to optimize performance and usability: Optimized Performance 🚀: BitNet.cpp is fine-tuned to run seamlessly on both ARM and x86 CPUs — commonly found in PCs and mobile devices. Performance gains are impressive 🔥; on ARM CPUs, speed increases range from 1.37x to 5.07x, and on x86 CPUs, up to 6.17x.
BitNet. PyTorch Implementation of the linear methods and model from the paper "BitNet: Scaling 1-bit Transformers for Large Language Models". Paper link: BitLinear = tensor -> layernorm -> Binarize -> abs max quantization -> dequant.
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27 kwi 2024 · BitNet. PyTorch Implementation of the linear methods and model from the paper "BitNet: Scaling 1-bit Transformers for Large Language Models" Paper link: BitLinear = tensor -> layernorm -> Binarize -> abs max quantization -> dequant.
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