Well, you can learn about generative models from MOOCs like the ones taught at UMich, Universitat Tubingen, or New York University (taught by Yann LeCun), and can gain knowledge there.
You can also watch the fast.ai MOOC titled Deep Learning from Scratch to Stable Diffusion [0].
You can also look at open source implementation of text2image models like Dall-E Mini or the works of lucid rain.
I worked on the Dall-E Mini project, and the technical knowhow that you need isn’t closely taught at MOOCs. You need to know, on top of Deep Learning theory, many tricks, gotchas, workarounds, etc.
You could follow the works of Eluther AI, follow Boris Dayma (project leader of Dall-E Mini) and Horace Ho on twitter. And any such people who have significant experience in practical AI and regularly share their tricks. The PyTorch forums is also a good place.
You can also watch the fast.ai MOOC titled Deep Learning from Scratch to Stable Diffusion [0].
You can also look at open source implementation of text2image models like Dall-E Mini or the works of lucid rain.
I worked on the Dall-E Mini project, and the technical knowhow that you need isn’t closely taught at MOOCs. You need to know, on top of Deep Learning theory, many tricks, gotchas, workarounds, etc.
You could follow the works of Eluther AI, follow Boris Dayma (project leader of Dall-E Mini) and Horace Ho on twitter. And any such people who have significant experience in practical AI and regularly share their tricks. The PyTorch forums is also a good place.
Learn PyTorch and/or JAX/Flax really well.
[0]: https://www.fast.ai/posts/part2-2022.html