Viewing profile — tama_sala

The library already has tinygrad support it seems, so it's not limited to Apple & MLX

You can use other models like a vision LLM, or use AI agents as well

The embedding size is only 8k so while the parameters are 70B. So it's a huge difference

This is the most relatable comment in this thread. I had the same experience when I was using ros.org and moved to a new distro

Correct, which one of the main moats Nvidia has when it comes to training

Potato/ Jerusalem artichoke ? (“Erdapfel”) is my fav