I'm trying to get up to speed on the subject of text2image and diffusion models. What are some good resources I should consult?
Here's what I've found helpful so far.
Fine tuning #stablediffusion to make Pokemon!
I wrote a quick guide on fine tuning your own Stable Diffusion: https://t.co/hLWrOjEPTm
I also released my Pokemon model, you can try it out on Replicate: https://t.co/3sVQrk54wZ
or with this Notebook: https://t.co/nRU5EQt3WC
Stable Diffusion concepts library https://t.co/X2jHPdWp4E textual inversion is amazing - can train a custom word vector (not otherwise reachable by english text) to mean a concept, based on examples. Opens up many possibilities of condensing objects/styles into special tokens 🚀
If you live in Toronto, we have a number of Public WiFi locations that you can connect to Beanfield WiFi for free. Here is a list of those locations: https://t.co/I8T4TYmMfw
I probably should have written this years ago, but here are some MLOps principles I think every ML platform (codebase, data management platform) should have: 1/n