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README.md
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This preview version is an intermediate model checkpoint, and is not representative of the final quality. The final version will improve, especially for fine details and overall aesthetics.
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#
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The model is natively supported in ComfyUI. The above image contains a workflow; you can open it in ComfyUI or drag-and-drop to get the workflow.
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#
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The model is trained on Danbooru-style tags, natural language captions, and combinations of tags and captions.
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##
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[quality/meta/year/safety tags] [1girl/1boy/1other etc] [character] [series] [artist] [general tags]
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Within each tag section, the tags can be in arbitrary order.
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Human score based: masterpiece, best quality, good quality, normal quality, low quality, worst quality
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PonyV7 aesthetic model based: score_9, score_8, ..., score_1
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You can use either the human score quality tags, the aesthetic model tags, both together, or neither. All combinations work.
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Specific year: year 2025, year 2024, ...
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Period: newest, recent, mid, early, old
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highres, absurdres, anime screenshot, jpeg artifacts, official art, etc
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safe, sensitive, nsfw, explicit
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Prefix artist with @. E.g. "@big chungus". **You must put @ in front of the artist.** The effect will be very weak if you don't.
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year 2025, newest, normal quality, score_5, highres, safe, 1girl, oomuro sakurako, yuru yuri, @nnn yryr, smile, brown hair, hat, solo, fur-trimmed gloves, open mouth, long hair, gift box, fang, skirt, red gloves, blunt bangs, gloves, one eye closed, shirt, brown eyes, santa costume, red hat, skin fang, twitter username, white background, holding bag, fur trim, simple background, brown skirt, bag, gift bag, looking at viewer, santa hat, ;d, red shirt, box, gift, fur-trimmed headwear, holding, red capelet, holding box, capelet
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##
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The model was trained with random tag dropout. You don't need to include every single relevant tag for the image.
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##
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To improve style and content diversity, the model was additionally trained on two non-anime datasets: LAION-POP (specifically the ye-pop version) and DeviantArt. Both were filtered to exclude photos. Because these datasets are qualitatively different from anime datasets, captions from them have been labeled with a "dataset tag". This occurs at the very beginning of a prompt followed by a newline. Optionally, the second line can contain either the image alt-text (ye-pop) or the title of the work (DeviantArt). Examples:
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Flame<br>
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Digital painting of a fiery dragon with glowing yellow eyes, black horns, and a long, sinuous tail, perched on a glowing, molten rock formation. The background is a gradient of dark purple to orange.
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#
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This model is licensed under the CircleStone Labs Non-Commercial License. The model and derivatives are only usable for non-commercial purposes. Additionally, this model constitutes a "Derivative Model" of Cosmos-Predict2-2B-Text2Image, and therefore is subject to the [NVIDIA Open Model License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/) insofar as it applies to Derivative Models.
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The details of the commercial licensing process are still being worked out. For now, you can express your interest in acquiring a commercial license by emailing tdrussell1@proton.me
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This preview version is an intermediate model checkpoint, and is not representative of the final quality. The final version will improve, especially for fine details and overall aesthetics.
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# Installing and running
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The model is natively supported in ComfyUI. The above image contains a workflow; you can open it in ComfyUI or drag-and-drop to get the workflow.
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# Prompting
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The model is trained on Danbooru-style tags, natural language captions, and combinations of tags and captions.
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## Tag order
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[quality/meta/year/safety tags] [1girl/1boy/1other etc] [character] [series] [artist] [general tags]
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Within each tag section, the tags can be in arbitrary order.
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## Quality tags
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Human score based: masterpiece, best quality, good quality, normal quality, low quality, worst quality
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PonyV7 aesthetic model based: score_9, score_8, ..., score_1
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You can use either the human score quality tags, the aesthetic model tags, both together, or neither. All combinations work.
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## Time period tags
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Specific year: year 2025, year 2024, ...
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Period: newest, recent, mid, early, old
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## Meta tags
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highres, absurdres, anime screenshot, jpeg artifacts, official art, etc
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## Safety tags
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safe, sensitive, nsfw, explicit
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## Artist tags
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Prefix artist with @. E.g. "@big chungus". **You must put @ in front of the artist.** The effect will be very weak if you don't.
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## Full tag example
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year 2025, newest, normal quality, score_5, highres, safe, 1girl, oomuro sakurako, yuru yuri, @nnn yryr, smile, brown hair, hat, solo, fur-trimmed gloves, open mouth, long hair, gift box, fang, skirt, red gloves, blunt bangs, gloves, one eye closed, shirt, brown eyes, santa costume, red hat, skin fang, twitter username, white background, holding bag, fur trim, simple background, brown skirt, bag, gift bag, looking at viewer, santa hat, ;d, red shirt, box, gift, fur-trimmed headwear, holding, red capelet, holding box, capelet
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## Tag dropout
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The model was trained with random tag dropout. You don't need to include every single relevant tag for the image.
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## Dataset tags
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To improve style and content diversity, the model was additionally trained on two non-anime datasets: LAION-POP (specifically the ye-pop version) and DeviantArt. Both were filtered to exclude photos. Because these datasets are qualitatively different from anime datasets, captions from them have been labeled with a "dataset tag". This occurs at the very beginning of a prompt followed by a newline. Optionally, the second line can contain either the image alt-text (ye-pop) or the title of the work (DeviantArt). Examples:
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Flame<br>
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Digital painting of a fiery dragon with glowing yellow eyes, black horns, and a long, sinuous tail, perched on a glowing, molten rock formation. The background is a gradient of dark purple to orange.
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# Limitations
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- The model doesn't do realism well. This is intended. It is an anime / illustration / art focused model.
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- The model may generate undesired content, especially if the prompt is short or lacking details.
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- Avoid this by using the appropriate safety tags in the positive and negative prompts, and by writing sufficiently detailed prompts.
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- The preview model isn't that good at higher resolutions yet.
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- It is a medium-resolution intermediate checkpoint, trained on a small amount of high-res images.
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- The final version will have been trained on a dedicated high-res phase. Details and overall image composition will improve.
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- The preview model is a true base model. It hasn't been aesthetic tuned on a curated dataset. The default style is very plain and neutral, which is especially apparent if you don't use artist or quality tags.
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# License
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This model is licensed under the CircleStone Labs Non-Commercial License. The model and derivatives are only usable for non-commercial purposes. Additionally, this model constitutes a "Derivative Model" of Cosmos-Predict2-2B-Text2Image, and therefore is subject to the [NVIDIA Open Model License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/) insofar as it applies to Derivative Models.
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The details of the commercial licensing process are still being worked out. For now, you can express your interest in acquiring a commercial license by emailing tdrussell1@proton.me
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