Quantized CPU model are up to 75% smaller, with 50% faster inference times
In this blog post, we will cover the Simple Contrastive Learning Representation Framework developed by Google, and implement SimCLR from scratch using PyTorch and PyTorch Lightning.
In this guest article from Fritz AI, we'll be outlining the key considerations in building a mobile-focused ML pipeline from end-to-end.
RAPIDS and RAPIDS accelerates workflows using classical machine learning techniques by a factor of 20x or more.
A guide to integrating Spell with your existing AWS services
Create an account in minutes or connect with our team to learn how Spell can accelerate your business.