Maintainer: IDEA-CCNL

Total Score


Last updated 5/28/2024


Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

The Taiyi-Stable-Diffusion-1B-Anime-Chinese-v0.1 model is the first open-source Chinese Stable Diffusion Anime model, trained on a dataset of 1 million low-quality and 10,000 high-quality Chinese anime image-text pairs. Developed by the IDEA-CCNL team, this model builds upon the pre-trained Taiyi-Stable-Diffusion-1B-Chinese-v0.1 model and further fine-tuned it on anime-specific data.

Model inputs and outputs


  • Textual Prompts: The model takes in textual prompts that describe the desired image content, using natural language.


  • Generated Images: The model outputs high-quality, photorealistic images that match the provided textual prompts.


The Taiyi-Stable-Diffusion-1B-Anime-Chinese-v0.1 model demonstrates strong capabilities in generating Chinese-inspired anime-style illustrations. The model is able to capture intricate details, realistic textures, and vibrant colors in the generated images. Additionally, the model retains the powerful generative abilities of the original Stable Diffusion model, allowing it to handle a wide range of prompts beyond just anime-themed content.

What can I use it for?

This model can be particularly useful for artists, designers, and content creators who want to generate high-quality Chinese anime-style illustrations. The model can be used to ideate new characters, scenes, and narratives, or to create visual assets for games, animations, and other multimedia projects. The open-source nature of the model also makes it accessible for educational and research purposes, enabling further exploration and development of text-to-image AI capabilities.

Things to try

One interesting aspect of the Taiyi-Stable-Diffusion-1B-Anime-Chinese-v0.1 model is its ability to seamlessly handle both Chinese and English prompts. This allows users to experiment with bilingual or multilingual prompts, potentially leading to unique and unexpected results. Additionally, users can try leveraging the model's strengths in generating anime-style art by incorporating detailed, descriptive prompts that capture the desired aesthetic and narrative elements.

This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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