What Google's TurboQuant can and can't do for AI's spiraling cost ...

TurboQuant vector quantization targets KV cache bloat, aiming to cut LLM memory use by 6x while preserving benchmark accuracy ...

Abstract: Remarkable achievements have been obtained with binary neural networks (BNN) in real-time and energy-efficient single-image super-resolution (SISR) methods. However, existing approaches ...

First, clone this repository to your local machine, and install the dependencies (torch, torchvision, numpy, Pillow, and huggingface_hub). git clone git@github.com ...

SD.Next Quantization provides full cross-platform quantization to reduce memory usage and increase performance for any device. Triton enables the use of optimized kernels for much better performance.