Search results
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).
This repository not only provides PyTorch implementations for training and evaluating 1.58-bit neural networks but also includes a unique integration where the experiments conducted automatically update a LaTeX-generated paper.
18 wrz 2024 · To overcome this limitation, we explored a few tricks that allow fine-tuning an existing model to 1.58 bits! Keep reading to find out how ! Table of Contents. TL;DR. What is BitNet in More Depth? Pre-training Results in 1.58b. Fine-tuning in 1.58b. Kernels used & Benchmarks. Conclusion. Acknowledgements. Additional Resources. TL;DR.
28 lut 2024 · Recent research, such as BitNet, is paving the way for a new era of 1-bit Large Language Models (LLMs). In this work, we introduce a 1-bit LLM variant, namely BitNet b1.58, in which every single parameter (or weight) of the LLM is ternary {-1, 0, 1}.
26 mar 2024 · BitNet b1.58 addresses this by halving activation bits, enabling a doubled context length with the same resources, with potential further compression to 4 bits or lower for 1.58-bit LLMs, a...
5 sie 2024 · The loss in capacity due to the 1.58-bit quantization can be offset by increasing the parameter count.
29 lut 2024 · BitNet b1.58 is not just an advancement in AI technology; it’s a testament to the untapped potential of efficiency-driven design in the realm of Large Language Models. As we embrace this new...
