Laionide (version 3)

Direct comparison to OpenAI’s model using COCO captions

Shout out to stability.ai for donating the compute to laion needed for this to be possible.

Files: - laionide-v3-base.pt

Inference: - replicate - colab - locally

Results: - comparison to openai W&B report

Notes: - You can use laionide-v2-sr.pt to upscale the outputs from laionide-v3-base.pt. - There are watermarks in some outputs. You can try to prompt engineer this away, but it isn’t always possible. royalty free seems to work well.

Training details: - finetuned laionide-v2-base.pt for 9 epochs on a subset of CC12M (~1.5 million pairs), COCO (~100K pairs), virtual genome (~100K pairs), and open images localized annotations (~800K pairs). - 20% of unconditional/empty token, per the paper.