Textual Inversion
Technique for teaching Stable Diffusion new concepts from a few images.
About
Textual Inversion is a technique that teaches a frozen text-to-image diffusion model a new concept, such as an object or style, from just three to five example images by learning a new pseudo-word in the model's embedding space. That learned word can then be composed into ordinary prompts to generate the concept in new scenes, a lightweight alternative to full fine-tuning. It is implemented in Diffusers and Stable Diffusion UIs.
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Details
- Category
- Model Training & Fine-Tuning
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Easy (2/5)
- Minimum VRAM
- 4 GB
- Added
- Apr 3, 2026
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