KerasHub enables users to mix and match model architectures and weights across different machine learning frameworks, allowing checkpoints from sources like Hugging Face Hub (including those created with PyTorch) to be loaded into Keras models for use with JAX, PyTorch, or TensorFlow. This flexibility means you can leverage a vast array of community fine-tuned models while maintaining full control over your chosen backend framework.
Using KerasHub for easy end-to-end machine learning workflows with Hugging Face
Related Posts
Celebrating Google Dev Library’s Women Contributors in AI/ML
Posted by Swathi Dharshna Subbaraj, Google Dev Library Women have made remarkable progress in advancing AI/ML technology through…
Hoisting of Variables, Functions, Classes, Types, Interfaces in JavaScript/TypeScript
In the world of JavaScript, understanding the concept of hoisting can significantly improve the way you write and…
Using Action Cable with React and Rails.
Intro Earlier this week I wanted to use Action Cable for its nice two way connections. I ended…
