Min-Illust-Background-Diffusion
Maintainer: ProGamerGov
59
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The Min-Illust-Background-Diffusion model is a fine-tuned version of the Stable Diffusion v1.5 model, trained by ProGamerGov on a selection of artistic works by Sin Jong Hun. This model was trained for 2250 iterations with a batch size of 4, using the ShivamShrirao/diffusers library with full precision, prior-preservation loss, the train-text-encoder feature, and the new 1.5 MSE VAE from Stability AI. A total of 4120 regularization / class images were used from this dataset.
Similar models like the Vintedois (22h) Diffusion model and the Stable Diffusion v1-4 model also use Stable Diffusion as a base, but are trained on different datasets and have their own unique characteristics.
Model inputs and outputs
Inputs
- Prompt: A text description that the model uses to generate the output image. The model responds best to prompts that include the token sjh style.
Outputs
- Image: A generated image that matches the prompt. The model outputs images at 512x512, 512x768, and 512x512 resolutions.
Capabilities
The Min-Illust-Background-Diffusion model is capable of generating artistic, landscape-style images that capture the aesthetic of the training data. The model performs well on prompts that steer the output towards specific artistic styles, even at a weaker strength. However, the model is not as well-suited for generating portraits and related tasks, as the training data was primarily composed of landscapes.
What can I use it for?
This model could be useful for projects that require the generation of landscape-style artwork, such as concept art, background designs, or illustrations. The ability to fine-tune the artistic style through prompt engineering makes it a flexible tool for creative applications.
However, due to the limitations around portrait generation, this model may not be the best choice for projects that require realistic human faces or characters. For those use cases, other Stable Diffusion-based models like Stable Diffusion v1-4 may be a better fit.
Things to try
One interesting aspect of this model is its ability to capture specific artistic styles through the use of the sjh style token in the prompt. Experimentation with this token and other style-specific keywords could lead to the generation of unique, visually striking artwork.
Additionally, exploring the model's ability to generate landscape-focused images with different perspectives, compositions, and lighting conditions could reveal its versatility and lead to the creation of compelling visual assets.
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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