Stable Diffusion models, starting with runwayml/stable-diffusion-v1-5, trained on images extracted from gifs from https://www.neopets.com/funimages.phtml. CLIP ViT-B/32 (OpenAI) was used to filter the best matching frame of the GIF for every given caption/GIF pair. In total this amounts to 1950 images around 100x100px. The DreamBooth models were finetuned at 448x448px on a Colab T4 with the term "low-resolution" concatenated onto every prompt, to hopefully combat artifacting in the final results (see this link for a hypothesis from someone on Discord about using negative terms while training Textual Inversions https://cdn.discordapp.com/attachments/1008246088148463648/1041538692432527470/image.png).
Example chosen frame of GIF from CLIP
| Caption | Unprocessed GIF | Chosen Frame |
|---|---|---|
| "yurble_baby_clap" |  |
 |
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