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README.md

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-Dreambooth models 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.
+Stable Diffusion models, starting with [runwayml/stable-diffusion-v1-5](https://huggingface.co/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).
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+Example chosen frame of GIF from CLIP
+| Caption | Unprocessed GIF | Chosen Frame |
+| --- | --- | --- |
+| "yurble_baby_clap" | ![](https://images.neopets.com/template_images/yurble_baby_clap.gif) | ![](https://cdn.discordapp.com/attachments/1010693530181718146/1043310485413576794/yurble_baby_clap.jpg) |
 
 "Don't forget, if you use these images on a non-Neopets page, you need to include our Copyright Notice." https://www.neopets.com/terms.phtml