this post was submitted on 28 Feb 2024
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LocalLLaMA

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Community to discuss about LLaMA, the large language model created by Meta AI.

This is intended to be a replacement for r/LocalLLaMA on Reddit.

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From the abstract: "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}."

Would allow larger models with limited resources. However, this isn't a quantization method you can convert models to after the fact, Seems models need to be trained from scratch this way, and to this point they only went as far as 3B parameters. The paper isn't that long and seems they didn't release the models. It builds on the BitNet paper from October 2023.

"the matrix multiplication of BitNet only involves integer addition, which saves orders of energy cost for LLMs." (no floating point matrix multiplication necessary)

"1-bit LLMs have a much lower memory footprint from both a capacity and bandwidth standpoint"

Edit: Update: additional FAQ published

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[–] [email protected] 3 points 9 months ago

My mind was already blown that models like Llama work with 4-bit quantization. But this is just insane.