elden-ring-diffusion

Maintainer: nitrosocke - Last updated 5/28/2024

🛸

Model overview

The elden-ring-diffusion model is a fine-tuned Stable Diffusion model trained on game art from the popular video game Elden Ring. This allows the model to generate images in the distinct style of the game's visuals. Similar models created by the same maintainer, nitrosocke, include Arcane Diffusion, Ghibli Diffusion, and Nitro Diffusion, each trained on different artistic styles.

Model inputs and outputs

The elden-ring-diffusion model takes text prompts as input and generates corresponding images in the style of Elden Ring. Users can influence the output by including the token _elden ring style_ in their prompts.

Inputs

  • Text prompts: Descriptive text that the model uses to generate images, e.g. "a magical princess with golden hair, elden ring style"

Outputs

  • Images: The generated images based on the provided text prompts, in the distinct visual style of Elden Ring.

Capabilities

The elden-ring-diffusion model can generate a wide variety of images, including portraits, landscapes, and fantastical scenes, all with the signature look and feel of the Elden Ring game world. The model is particularly adept at capturing the atmospheric, somber, and ominous tone that permeates the Elden Ring aesthetic.

What can I use it for?

The elden-ring-diffusion model can be a powerful tool for artists, designers, and content creators who want to incorporate the Elden Ring visual style into their projects. This could include creating concept art, promotional materials, fan art, and more. The model's ability to generate images quickly and with high fidelity makes it a valuable asset for those working in the fantasy and gaming spaces.

Things to try

One interesting aspect of the elden-ring-diffusion model is its ability to blend the Elden Ring style with other artistic influences. By combining the _elden ring style_ token with other keywords, users can experiment with mixing the game's visuals with other aesthetic elements, such as different character archetypes or environmental settings. This can lead to the creation of unique and unexpected imagery that captures the essence of Elden Ring while introducing new creative twists.



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

Total Score

321

Follow @aimodelsfyi on 𝕏 →

Related Models

Total Score

749

Arcane-Diffusion

nitrosocke

Arcane-Diffusion is a fine-tuned version of the Stable Diffusion model, trained on images from the TV show Arcane. This model can produce images in the distinctive "Arcane style" by using the tokens arcane style in your prompts. The maintainer nitrosocke has also created other fine-tuned Stable Diffusion models, such as mo-di-diffusion which is trained on images in a "modern Disney style". Model inputs and outputs Arcane-Diffusion is a text-to-image model that takes a text prompt as input and generates a corresponding image as output. The model can be used just like the original Stable Diffusion model, with the addition of the arcane style token to produce images in the Arcane aesthetic. Inputs Text prompt: A text description of the desired image, including the **arcane style token. Outputs Generated image**: An image that corresponds to the input text prompt, rendered in the Arcane art style. Capabilities Arcane-Diffusion can generate a wide variety of Arcane-themed images, from fantastical characters and creatures to elaborate environments and scenes. The model is able to capture the distinct visual style of the Arcane universe, including its unique color palette, lighting, and artistic flourishes. What can I use it for? Arcane-Diffusion can be used to create original artwork and illustrations inspired by the Arcane universe. This could include character designs, background environments, promotional materials, and more. The model can also be used to generate images for creative projects, such as fanart, game assets, or digital art commissions. Things to try One interesting aspect of Arcane-Diffusion is its ability to blend the Arcane art style with other elements. Try combining the arcane style token with prompts that introduce other themes, such as "a magical princess with golden hair, arcane style" or "a cyberpunk city at night, arcane style". This can lead to unique and unexpected results that push the boundaries of the model's capabilities.

Read more

Updated 5/28/2024

Text-to-Image

Total Score

345

spider-verse-diffusion

nitrosocke

spider-verse-diffusion is a fine-tuned Stable Diffusion model trained on movie stills from Sony's Into the Spider-Verse. This model can be used to generate images in the distinctive visual style of the Spider-Verse animated film using the spiderverse style prompt token. Similar fine-tuned models from the same maintainer, nitrosocke, include Arcane-Diffusion, Ghibli-Diffusion, elden-ring-diffusion, and mo-di-diffusion, each trained on a different animation or video game art style. Model inputs and outputs The spider-verse-diffusion model takes text prompts as input and generates corresponding images in the Spider-Verse visual style. Sample prompts might include "a magical princess with golden hair, spiderverse style" or "a futuristic city, spiderverse style". The model outputs high-quality, detailed images that capture the unique aesthetic of the Spider-Verse film. Inputs Text prompts describing the desired image content and style Outputs Images generated from the input prompts, in the Spider-Verse art style Capabilities The spider-verse-diffusion model excels at generating compelling character portraits, landscapes, and scenes that evoke the vibrant, dynamic visuals of the Into the Spider-Verse movie. The model is able to capture the distinct animated, comic book-inspired look and feel, with stylized character designs, bold colors, and dynamic camera angles. What can I use it for? This model could be useful for creating fan art, illustrations, and other creative content inspired by the Spider-Verse universe. The distinctive visual style could also be incorporated into graphic design, concept art, or multimedia projects. Given the model's open-source license, it could potentially be used in commercial applications as well, though certain usage restrictions apply as specified in the CreativeML OpenRAIL-M license. Things to try Experiment with different prompts to see how the model captures various Spider-Verse elements, from characters and creatures to environments and cityscapes. Try combining the spiderverse style token with other descriptors to see how the model blends styles. You could also try using the model to generate promotional materials, book covers, or other commercial content inspired by the Spider-Verse franchise.

Read more

Updated 5/28/2024

Text-to-Image

Total Score

607

Ghibli-Diffusion

nitrosocke

The Ghibli-Diffusion model is a fine-tuned Stable Diffusion model trained on images from modern anime feature films from Studio Ghibli. This model allows users to generate images in the distinct Ghibli art style by including the ghibli style token in their prompts. The model is maintained by nitrosocke, who has also created similar fine-tuned models like Mo Di Diffusion and Arcane Diffusion. Model inputs and outputs The Ghibli-Diffusion model takes text prompts as input and generates high-quality, Ghibli-style images as output. The model can be used to create a variety of content, including character portraits, scenes, and landscapes. Inputs Text Prompts**: The model accepts text prompts that can include the ghibli style token to indicate the desired art style. Outputs Images**: The model generates images in the Ghibli art style, with a focus on high detail and vibrant colors. Capabilities The Ghibli-Diffusion model is particularly adept at generating character portraits, cars, animals, and landscapes in the distinctive Ghibli visual style. The provided examples showcase the model's ability to capture the whimsical, hand-drawn aesthetic of Ghibli films. What can I use it for? The Ghibli-Diffusion model can be used to create a wide range of Ghibli-inspired content, from character designs and fan art to concept art for animation projects. The model's capabilities make it well-suited for creative applications in the animation, gaming, and digital art industries. Users can also experiment with combining the Ghibli style with other elements, such as modern settings or fantastical elements, to generate unique and imaginative images. Things to try One interesting aspect of the Ghibli-Diffusion model is its ability to generate images with a balance of realism and stylization. Users can try experimenting with different prompts and negative prompts to see how the model handles a variety of subjects and compositions. Additionally, users may want to explore how the model performs when combining the ghibli style token with other artistic styles or genre-specific keywords.

Read more

Updated 5/28/2024

Text-to-Image

🔗

Total Score

141

redshift-diffusion-768

nitrosocke

The redshift-diffusion-768 model is a fine-tuned version of the Stable Diffusion 2.0 model, trained on high-quality 3D images with a 768x768 pixel resolution. It was developed by the Hugging Face creator nitrosocke. This model can produce images in a unique "redshift style" by using the prompt tokens redshift style. Similar models include the Ghibli-Diffusion, elden-ring-diffusion, mo-di-diffusion, Arcane-Diffusion, and Nitro-Diffusion, all of which are fine-tuned on different art styles and datasets. Model inputs and outputs The redshift-diffusion-768 model takes text prompts as input and generates corresponding images as output. The text prompts can describe a wide variety of subjects, including characters, scenes, and objects, and the model will attempt to render them in the unique "redshift style". Inputs Text prompt**: A description of the desired image, using the redshift style tokens for the specific effect. Outputs Image**: A generated image that matches the provided text prompt, rendered in the "redshift style". Capabilities The redshift-diffusion-768 model can generate highly detailed and visually striking images in a wide range of subjects, from characters and portraits to landscapes and scenes. The "redshift style" gives the images a distinct look, with vibrant colors, strong lighting, and a futuristic or science-fiction aesthetic. What can I use it for? The redshift-diffusion-768 model can be used for a variety of creative and artistic applications, such as concept art, character design, and world-building for science-fiction or fantasy projects. The unique visual style of the model's outputs could also be leveraged for commercial applications, such as product design, advertising, or visual effects. Things to try One interesting aspect of the redshift-diffusion-768 model is its ability to generate highly detailed and visually striking images with a wide range of subjects. Try experimenting with different types of prompts, from detailed character descriptions to abstract or surreal scenes, to see the versatility of the model's capabilities. Additionally, you can try mixing the "redshift style" with other art styles, such as those from the Ghibli-Diffusion or Elden Ring Diffusion models, to create unique and unexpected visual combinations.

Read more

Updated 5/28/2024

Image-to-Image