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 ...

Running large language models on local hardware not only lets you avoid paying monthly subscriptions to cloud providers, but also prevents large corporations from gaining access to your private data.

The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...