its cool to see the iterative improvements to your model laid out, but for everything that workedm i imagine there were at least a million other things you also tried but didnt work out. whats your process of trying these different techniques/architectures? do you just wait for one experiment to finish and visually inspect the results everytime. seems hard since these take a while to train. how do you shorten the feedback loop in this space?

Very nice well written article!

The kind that I like so much on HN. It tickle your mind but is still clear enough for an advanced beginner.

Hi HN, I’m one of the two authors of the post and the Linum v2 text-to-video model (https://news.ycombinator.com/item?id=46721488). We're releasing our Image-Video VAE (open weights) and a deep dive on how we built it. Happy to answer questions about the work!

Nice summary! I missed the mention of EQ-VAE when it comes to generation quality. Tiny trick, huge impact! Have you tried it?

This seems like a great model to experiment fine tuning with original art, given it’s relatively small and with open license. Is that a fair assessment?

Thanks for the great write up and making it available to us all.

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