TencentARC/T2I-Adapter

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

3801 stars · 226 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Official implementation of T2I-Adapter, lightweight adapter models that add controllable conditioning (sketch, canny, lineart, depth, pose) to text-to-image diffusion models like Stable Diffusion XL. It integrates with Hugging Face diffusers and provides pretrained adapter checkpoints and demos.

Use cases

• control stable diffusion image generation with a sketch
• generate images guided by depth maps or canny edges
• add pose conditioning to SDXL text-to-image generation
• use lightweight adapters for controllable diffusion models in diffusers
• turn line art into fully rendered images with AI

When to choose

• you need lightweight, efficient conditioning adapters for SD 1.4/1.5 or SDXL
• you already use Hugging Face diffusers and want T2I-Adapter support
• you want sketch, edge, depth, or pose control over text-to-image generation

When to avoid

• you need actively developed features or guaranteed support (no license file, limited maintenance)
• you prefer ControlNet-style heavier conditioning with broader community tooling
• you need non-Python or production-served inference out of the box

Facets

library · maturity maintenance

machine-learning deep-learning image-processing stable-diffusion artificial-intelligence deep-learning image-processing computer-vision python text-to-image diffusion-models controllable-generation adapters sdxl stable-diffusion sketch-to-image research gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="TencentARC/T2I-Adapter")