LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale 9 sources These sources collectively discuss LLM.int8(), a quantization method that enables large language models (LLMs) to run efficiently on more accessible hardware, such as consumer GPUs, without degrading performance. The core of this technique involves 8-bit matrix multiplication, which significantly reduces memory footprint by converting model weights to lower precision. A key innovation in LLM.int8() is its handling of "outlier features" through a mixed-precision decomposition that performs some computations in 16-bit precision while the majority remain in 8-bit. The bitsandbytes library is highlighted as a critical tool for implementing these quantization techniques, including newer 4-bit methods like QLoRA, which further reduce memory usage and facilitate fine-tuning of enormous models.