instantX-research/InstantStyle

Health v2 · maintenance only

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Adoption not part of the score

2018 stars · 125 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

InstantStyle is a framework for style-preserving text-to-image generation that disentangles style and content from reference images using feature-space subtraction and style-block-only injection into diffusion models. It is supported natively in Hugging Face diffusers and targets tuning-free image personalization.

Use cases

• transfer the style of a reference image to new generated images
• generate images in a specific artistic style without training
• apply a style to text-to-image output without content leakage
• stylize photos with stable diffusion and sdxl
• avoid weight tuning when using ip-adapter style transfer

When to choose

• you want tuning-free style transfer with diffusion models
• you need style and content disentanglement from a reference image
• you already use diffusers and want native style injection

When to avoid

• you need a production system with a maintained license
• you want non-diffusion image stylization
• you need guaranteed long-term support

Facets

library · maturity active

image-processing machine-learning stable-diffusion artificial-intelligence image-processing deep-learning python cross-platform text-to-image style-transfer diffusion-models tuning-free research gpu

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