DiffQ: Differentiable Quantization Framework for PyTorch

DiffQ is a differentiable quantization framework for PyTorch that provides tools to quantize PyTorch models, primarily focusing on large language models (LLMs) and computer vision models. It enables quantization-aware training and leverages various quantization methods like GPTQ, HQQ, and AWQ. Currently at version 0.2.4, it has seen active development, especially in late 2023, with periodic releases addressing new features and bug fixes.