instant-id-albedobase-xl
Maintainer: tgohblio
41
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Model overview
instant-id-albedobase-xl is a state-of-the-art AI model for zero-shot identity-preserving generation. Developed by the InstantX Team at Xiaohongshu Inc., it uses the AlbedoBase-XL v2.0 as its base model and incorporates proprietary techniques like LCM-LoRA acceleration and multi-ControlNets to achieve fast, high-quality results.
This model is similar to other InstantID variants like instant-id-multicontrolnet, instant-id-photorealistic, and instant-id-artistic. It also shares some similarities with the latent-consistency-model in terms of speed and control.
Model inputs and outputs
instant-id-albedobase-xl takes in an input image, prompt, and various settings to control the generation process. It outputs a new image that preserves the identity of the input face while stylizing it based on the given prompt.
Inputs
- Image: The input face image to use as a reference for identity preservation.
- Prompt: The text prompt describing the desired style and attributes for the generated image.
- Negative Prompt: The text prompt describing what should be avoided in the generated image.
- Width/Height: The desired dimensions of the output image.
- Guidance Scale: The scale for classifier-free guidance, with an optimum range of 0-5 when using LCM-LoRA.
- Safety Checker: A flag to enable or disable the built-in safety checker.
- IP Adapter Scale: The scale for the Identity Preserving Adapter, which controls the balance between identity preservation and style.
- Num Inference Steps: The number of denoising steps, with an optimum range of 6-8 when using LCM-LoRA.
- Controlnet Conditioning Scale: The scale for the ControlNet conditioning, which affects the balance between the input face and the generated style.
Outputs
- Output Image: The generated image that preserves the identity of the input face while matching the desired style and attributes.
Capabilities
instant-id-albedobase-xl is capable of generating high-quality, identity-preserving images in a matter of seconds. It can handle a wide range of styles and attributes, from photorealistic to artistic. The model's ability to balance identity preservation and style integration sets it apart from previous state-of-the-art techniques.
What can I use it for?
This model can be useful for various applications, such as:
- Portrait Generation: Create stylized portraits of real people for use in art, design, or entertainment projects.
- Character Design: Generate custom character designs with a consistent identity, but diverse styles.
- Content Creation: Quickly produce visually striking images for blogs, social media, or other online content.
- Personalized Marketing: Create unique, identity-based visuals for personalized advertising or branding campaigns.
Things to try
One key advantage of instant-id-albedobase-xl is its compatibility with LCM-LoRA, which allows for significantly faster inference times without sacrificing quality. By adjusting the guidance scale and number of inference steps, you can find the sweet spot between speed and fidelity for your specific use case.
Additionally, experiment with different base models and ControlNet configurations to achieve unique styles and better integration between the face and background. The maintainer's Hugging Face profile can be a useful resource for exploring these options.
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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