Maintainer: haor

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 Evt_V4-preview model is an experimental text-to-image diffusion model created by maintainer haor that is focused on generating animation-style images. It is part of the EVT series, which aims to fine-tune large datasets to produce diverse artistic styles. Compared to previous EVT models, Evt_V4-preview uses an even larger dataset, resulting in images that have a cosine similarity of 85% with the ACertainty model.

Similar models include Stable Diffusion v1-4, a general-purpose text-to-image diffusion model, and Epic Diffusion, a highly customized version of Stable Diffusion aimed at producing high-quality results in a wide range of styles.

Model inputs and outputs


  • Prompt: A text description of the desired image, which can include specific details about the content, style, and artistic references.


  • Image: A generated image that corresponds to the provided text prompt. The model can produce images in a variety of artistic styles, including animation-influenced aesthetics.


The Evt_V4-preview model is capable of generating diverse, artistically-styled images from text prompts. The model excels at producing anime-inspired artwork, as evidenced by the provided samples that feature detailed characters, fantastical environments, and a vibrant color palette.

What can I use it for?

The Evt_V4-preview model is well-suited for artistic and creative applications, such as generating concept art, character designs, and illustrations. It could be used to quickly produce draft images for creative projects or as a tool for ideation and exploration. However, the model's capabilities are not limited to animation-style art, and it may be able to generate images in a range of other artistic genres as well.

Things to try

One interesting aspect of the Evt_V4-preview model is its potential to generate unique animation-inspired styles that differ from traditional anime or manga aesthetics. Experimenting with different prompts that blend various artistic influences, such as combining anime elements with western comic book styles or surreal, dreamlike compositions, could yield intriguing results. Additionally, trying the model with prompts that focus on less common subject matter, such as sci-fi or fantasy settings, might uncover new creative directions for the model's animation-influenced capabilities.

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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