--- license: mit datasets: - hearmeneigh/e621-rising-v3-curated - hearmeneigh/e621-rising-v3-finetuner library_name: diffusers pipeline_tag: text-to-image tags: - anthro - furry - e621 - nsfw - booru - imagebooru - imageboard - gelbooru - danbooru - rule34 - not-for-all-audiences ---

NSFW

This model is not suitable for use by minors. The model can and will produce X-rated/NFSW content.

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Tag Autocomplete CSV

Reference

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What's new in v3?
Prompt examples
Prompt guide
Tag list
Tag autocomplete guide
# E621 Rising V3 (SDXL) * Furry / anthro base model trained with images (mainly) from [E621](https://e621.net) * Guaranteed **NSFW** or your money back * Stable Diffusion XL 1.0 model: * `1024x1024px` * Trained with 11 epochs of 280,000 images each * Finetuned with 16 epochs of 40,000 images each * Compatible with [🤗 `diffusers`](https://huggingface.co/docs/diffusers/index) * Compatible with [`stable-diffusion-webui`](https://github.com/AUTOMATIC1111/stable-diffusion-webui) * Fully open source crawl, dataset, curation, and training process: * Use these tools to train your own version with your own dataset! * [Configuration](https://github.com/hearmeneigh/e621-rising-configs) * [Toolchain](https://github.com/hearmeneigh/dataset-rising) * [Dataset](https://huggingface.co/datasets/hearmeneigh/e621-rising-v3-curated) ## Training Procedure [Training legend](TBD) * 160 images per batch (epoch variant) * `1024x1024px` image size * Adam optimizer * Beta1 = `0.9` * Beta2 = `0.999` * Weight decay = `1e-2` * Epsilon = `1e-08` * Constant learning rate `4e-6` * `fp16` mixed precision * SNR gamma set to `5.0` * Noise offset set to `0.07` * `cosine_with_restarts` scheduler * 11 epochs of [V3 curated dataset](https://huggingface.co/datasets/hearmeneigh/e621-rising-v3-curated) samples resized to `< 1024x1024px` (maintain aspect ratio) * 16 epochs of [V3 finetuner dataset](https://huggingface.co/datasets/hearmeneigh/e621-rising-v3-finetuner) samples resized to `< 1024x1024px` (maintain aspect ratio) * Tags for each sample are shuffled for each epoch