Introducing the Unify LLM Hub

If the last century has taught us anything about intelligence, it's that general intelligence is always an emergent property of an optimization algorithm. It is not hand crafted or hand engineered, it just pops out from a simple set of rules mixed with a lot of data and compute...

Tensorization is a model compression technique that breaks down weight tensors of deep neural networks into smaller, lower rank tensors to reveal underlying patterns and reduce...

In the previous blog post of our model compression series we went over the available quantization libraries and their features. In a similar fashion, we will now go over the packages and...

The LLM landscape is incredibly fast moving, with new models coming out every week. In the last few weeks alone, Mamba showed that structured state space models are more...

Following up with our model compression blog post series, we will now delve into quantization, one of the more powerful compression techniques that we can leverage to reduce the size and memory footprint of our models.‍Going forward, we will assume that you have read the first blog post of the series, where we introduced the concept of quantization. Building on top of this introduction....

One of the key drivers behind the rapid expansion in machine learning growth is the technological progress made in the development of...

AI has been in an ever expanding renaissance for the past decade, with the success of AlexNet being a pivotal moment which sparked a new wave of deep learning research in 2012. Since then, there have been several step change moments, such as the success of reinforcement learning algorithms on...

Machine learning has witnessed a surge in interest in recent years driven by several factors. including the availability of large datasets, advancements in transfer learning...

Machine learning (ML) models are becoming more complex and data-intensive, requiring more expensive hardware and infrastructure to train and run. As a result...