Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...

Perplexity was great—until my local LLM made it feel unnecessary ...

Researchers at Nvidia have developed a novel approach to train large language models (LLMs) in 4-bit quantized format while maintaining their stability and accuracy at the level of high-precision ...

Local LLMs are incredibly powerful tools, but it can be hard to put smaller models to good use in certain contexts. With fewer parameters, they often know less, though you can improve their ...