trinart_characters_19.2m_stable_diffusion_v1

Maintainer: naclbit

Total Score

170

Last updated 5/28/2024

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

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Model overview

trinart_characters_19.2m_stable_diffusion_v1 is a Stable Diffusion v1-based model trained on a dataset of roughly 19.2 million anime and manga-style images. This model aims to strike a balance between artistic style versatility and anatomical quality within the Stable Diffusion v1 specification. It is an evolution of the original TrinArt model that was used in the AI Novelist/TrinArt service from early September to October 2022. The newer Derrida model has since been released, which focuses more on anatomical stability compared to the v1 model.

Model inputs and outputs

The trinart_characters_19.2m_stable_diffusion_v1 model is a text-to-image diffusion model. It takes in a text prompt as input and generates a corresponding image as output.

Inputs

  • Text prompt: A natural language description of the desired image.

Outputs

  • Image: The generated image corresponding to the input text prompt.

Capabilities

The trinart_characters_19.2m_stable_diffusion_v1 model can generate a wide variety of anime and manga-style images based on the provided text prompt. Examples include characters, scenes, and environments in the distinctive Japanese art style. The model has been designed to produce anatomically plausible results while retaining the flexibility and creativity of the anime genre.

What can I use it for?

The trinart_characters_19.2m_stable_diffusion_v1 model can be a valuable tool for artists, designers, and creators looking to generate anime and manga-inspired artwork. It could be used to concept character designs, storyboard scenes, or explore new creative ideas. The model's versatility also makes it suitable for use in educational or artistic applications that aim to capture the aesthetic of Japanese visual culture.

Things to try

One interesting aspect of the trinart_characters_19.2m_stable_diffusion_v1 model is its ability to balance artistic style and anatomical accuracy. Experimenting with prompts that challenge this balance, such as those involving complex character poses or intricate backgrounds, can yield intriguing results that showcase the model's strengths and limitations. Additionally, using the provided negative prompts can help stabilize the generated images and refine the overall aesthetic.



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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