An Implementation of NanoQuant: A flexible binary quantization method

In three linesNanoQuant is a post-training quantization method compressing dense transformer models to 1-bit and sub-1-bit per weight. The implementation uses factorization into binary matrices with scaling vectors, achieving compression ratios up to 16x on f16 matrices. A fine-tuning step is required to align quantized outputs with unquantized ones.

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