I enjoy doing local image generation and this is one thing that the community around that has really optimized.
In some workflows you might have 20 different models doing their specialized tasks. Pose detection, hand/eye/face detailers, classifiers, refiners, up scalers, taggers, etc can all use their own models and that’s not even the including the model(s) used for the actual image generation part.
I’m interested to see the optimization when this concept gets applied to other general ai tasks.
Hmm is there a technical write up of how you are pulling this data?
I tried one of our companies for fun and it’s only pulling 1.4million records in one place and then 65,000 in another. Doesn’t seem to have all our nameservers or relays either.
In some workflows you might have 20 different models doing their specialized tasks. Pose detection, hand/eye/face detailers, classifiers, refiners, up scalers, taggers, etc can all use their own models and that’s not even the including the model(s) used for the actual image generation part.
I’m interested to see the optimization when this concept gets applied to other general ai tasks.