This is a simplified guide to an AI model called T2i-Adapter-Sdxl-Sketch maintained by Adirik. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
Model overview
The t2i-adapter-sdxl-sketch model is a text-to-image diffusion model that allows users to modify images using sketches. It is an implementation of the T2I-Adapter-SDXL model, developed by TencentARC and the diffuser team. This model is part of a family of similar models, including t2i-adapter-sdxl-lineart, t2i-adapter-sdxl-depth-midas, t2i-adapter-sdxl-canny, and t2i-adapter-sdxl-openpose, all created by adirik.
Model inputs and outputs
The t2i-adapter-sdxl-sketch model takes in an input image and a text prompt, and generates a modified image based on the provided prompt. The model can generate multiple samples, controlled by the num_samples parameter. The model also allows for fine-tuning of the generation process through parameters like guidance_scale, num_inference_steps, adapter_conditioning_scale, and adapter_conditioning_factor.
Inputs
- Image: The input image to be modified
- Prompt: The text prompt describing the desired modifications
- Scheduler: The scheduler to use for the diffusion process
- Num Samples: The number of output images to generate
- Random Seed: A seed for reproducibility
- Guidance Scale: The scale to match the prompt
- Negative Prompt: Specify things to not see in the output
- Num Inference Steps: The number of diffusion steps
- Adapter Conditioning Scale: The conditioning scale for the adapter
- Adapter Conditioning Factor: The factor to scale the image by
Outputs
- Output Images: The modified images generated by the model, based on the input prompt and image.
Capabilities
The t2i-adapter-sdxl-sketch model ca...
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