rinongal/textual_inversion

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

3055 stars · 284 forks observed · 2026-08-28

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

Official implementation of the Textual Inversion paper, which learns new word embeddings in a frozen text-to-image (Latent Diffusion) model from 3-5 example images to capture user-specific concepts. It provides training scripts, configs, and sample inversions for personalized image generation.

Use cases

• teach a text-to-image model my own concept from a few photos
• learn a new token embedding for a custom object or style
• generate images of a specific subject in new scenes
• invert a small image set into a diffusion model embedding
• personalize latent diffusion text-to-image generation

When to choose

• you want the original, paper-faithful textual inversion implementation for Latent Diffusion models
• you need to reproduce research results or build on the paper's method
• you work with the LDM text-to-image checkpoint and want embedding-based personalization

When to avoid

• you mainly want Stable Diffusion personalization in production - newer tools like diffusers or kohya trainers are better maintained
• you need pre-trained embeddings or polished tooling - several TODO items were never completed
• you want a no-training prompt-based approach rather than embedding optimization

Facets

library · maturity maintenance

llm-training machine-learning deep-learning stable-diffusion image-processing deep-learning machine-learning artificial-intelligence image-processing python textual-inversion text-to-image latent-diffusion personalization research-code embeddings diffusion-models gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="rinongal/textual_inversion")