8-bit Matrix Multiplication for Large Models

Hugging Face integrates 8-bit matrix multiplication (LLM.int8()) into its Transformers library, significantly reducing memory usage for large language models with minimal performance degradation. This enables running larger models on less hardware, making them more accessible for inference and fine-tuning. The integration leverages the bitsandbytes library and is supported by the Accelerate library for seamless usage across different hardware configurations. This post introduces Quantization-Aware Healing, a compressed, 4-bit model that outperforms its full-precision original, demonstrating further advancements in model compression and performance.