Perfectly compatible: just keep all modifications to the original code in public. AGPL does not mean that all code from your company must be open-source, just whatever is in the same binary/program as the AGPL one.
AGPL really is a great license for this type of project. It maximizes the power of everyone without limiting fair commercial use.
It can do humans in passive poses, but ask for an action shot and it botches it badly. It needs more training data on how bodies move. Maybe load it up with stills from dance, martial arts, and sports.
But seriously, it's open-source, so it hardly matters.
> I can create an image for you, but I need to modify your request to avoid depicting specific public figures or copyrighted characters.
It took effort for even "Chinese leader".
It also has the same idea as Dalle 3 to train the model on synthetic captions.
>This integration allows running the pipeline with a batch size of 4 under 11 GBs of GPU VRAM. GPU VRAM consumption under 10 GB will soon be supported, too. Stay tuned.
- Existing models for data pseudo-labelling
- ImageNet pretraining
- A frozen text encoder
- A frozen image encoder
