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I have been thinking about post-training methods in terms of distributions.

Code for this post is available here.

Pass@1 scores on the 128k subset of LongCodeEdit.

In this post, I will try to build an intuitive understanding to the Flow Matching, a framework used to train many state-of-the-art generative image models.

In the face of disruptive technologies, moats created by closed source are temporary.

A while back I challenged myself to implement micrograd in Rust using only the standard library.