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cs.LG2024
When are 1.58 bits enough? A Bottom-up Exploration of BitNet Quantization
Jacob Nielsen, Lukas Galke, Peter Schneider-Kamp
Contemporary machine learning models, such as language models, are powerful, but come with immense resource requirements both at training and inference time. It has been shown that…
cs.CV2024
BitNet b1.58 Reloaded: State-of-the-art Performance Also on Smaller Networks
Jacob Nielsen, Peter Schneider-Kamp
Recently proposed methods for 1-bit and 1.58-bit quantization aware training investigate the performance and behavior of these methods in the context of large language models, find…