Ostris

Models by this creator

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ikea-instructions-lora-sdxl

ostris

Total Score

197

The ikea-instructions-lora-sdxl model is a LORA (Low-Rank Adaptation) model trained on SDXL (Stable Diffusion XL) to generate images that follow step-by-step instructions. This model was created by ostris, who maintains the model on Hugging Face. The model is able to generate images that depict specific steps or actions, such as assembling furniture, cooking a hamburger, or recreating scenes from movies. It can take simple prompts describing the desired outcome and generate the corresponding step-by-step visual instructions. Compared to similar models like the sdxl-wrong-lora and the Personal_Lora_collections, the ikea-instructions-lora-sdxl model is specifically focused on generating step-by-step visual instructions rather than character-focused or general image generation. Model inputs and outputs Inputs Prompt**: A simple text description of the desired outcome, such as "hamburger" or "sleep". Negative prompt** (optional): Words to avoid in the generated images, such as "blurry" or "low quality". Outputs Step-by-step images**: The model generates a series of images that visually depict the steps to achieve the desired outcome described in the prompt. Capabilities The ikea-instructions-lora-sdxl model excels at generating clear, step-by-step visual instructions for a wide variety of tasks and objects. It can take simple prompts and break them down into a series of instructional images, making it useful for tasks like assembling furniture, cooking recipes, or recreating scenes from movies or books. For example, with the prompt "hamburger, lettuce, mayo, lettuce, no tomato", the model generates a series of images showing the steps to assemble a hamburger with the specified toppings. Similarly, the prompt "barbie and ken" results in a series of images depicting a Barbie and Ken doll scene. What can I use it for? The ikea-instructions-lora-sdxl model could be useful for a variety of applications, such as: Instructional content creation**: Generate step-by-step visual instructions for assembling products, cooking recipes, or completing other tasks. Educational resources**: Create interactive learning materials that visually demonstrate concepts or processes. Entertainment and media**: Generate visuals for storytelling, creative projects, or movie/TV show recreations. ostris, the maintainer of the model, suggests that it can be useful for a wide range of prompts, and that the model is able to "figure out the steps" to create the desired images. Things to try One interesting aspect of the ikea-instructions-lora-sdxl model is its ability to take simple prompts and break them down into a series of instructional images. Try experimenting with different types of prompts, from everyday tasks like "make a sandwich" to more complex or creative prompts like "the dude, from the movie the big lebowski, drinking, rug wet, bowling ball". Additionally, you can explore the use of negative prompts to refine the generated images, such as avoiding "blurry" or "low quality" outputs. This can help the model generate cleaner, more polished instructional images.

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Updated 5/28/2024

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ip-composition-adapter

ostris

Total Score

152

The ip-composition-adapter is a unique AI model designed to inject the general composition of an image into the Stable Diffusion 1.5 and SDXL models, while mostly ignoring the style and content. This means that an input image of a person waving their left hand can produce an output image of a completely different person waving their left hand. This sets it apart from control nets, which are more rigid and aim to spatially align the output image to the control image. The model was created by ostris, who gives full credit to POM and BANODOCO for the original idea. It can be used similarly to other IP+ adapters from the h94/IP-Adapter repository, requiring the CLIP vision encoder (CLIP-H). Model inputs and outputs Inputs Prompt**: The text prompt describing the desired image Control Image**: An image that provides the general composition for the output Outputs Generated Image**: A new image that matches the provided prompt and the general composition of the control image Capabilities The ip-composition-adapter allows for more flexible control over the composition of generated images compared to control nets. Rather than rigidly aligning the output to the control image, it uses the control image to influence the overall composition while still generating a unique image based on the input prompt. What can I use it for? The ip-composition-adapter could be useful for creative projects where you want to generate images that follow a specific composition, but with different subject matter. For example, you could use a portrait of a person waving as the control image, and generate a variety of different people waving in that same pose. This could be beneficial for designers, artists, or anyone looking to create a consistent visual style across a series of images. Things to try One interesting aspect of the ip-composition-adapter is its ability to generate images that maintain the overall composition but with completely different subject matter. You could experiment with using a wide variety of control images, from landscapes to abstract patterns, and see how the generated images reflect those underlying compositions. This could lead to some unexpected and creative results.

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Updated 5/28/2024