name: custom-diffusion
description: "Route Custom Diffusion workflows for concept data prep, diffusers
training and SDXL, sample generation, delta tools, and CustomConcept101
evaluation."
disable-model-invocation: true
metadata:
disco-role: operating
license: NOASSERTION
Custom Diffusion
Use this repo skill for the diffusers-side Custom Diffusion workflow family:
- prepare concept data and real-prior bundles
- train single- and multi-concept models with diffusers or SDXL
- sample from delta checkpoints
- extract, compress, and compose delta artifacts
- evaluate generated samples on CustomConcept101
Start here
- Read
references/repo-provenance.md to confirm the source baseline.
- Read
references/workflows.md for the route map.
- Run
scripts/check_runtime.py --require-cuda to confirm the CUDA/import stack.
- Use
scripts/validate_concepts.py when a concept-list JSON needs a structural check.
- Open the focused sub-skill for the task family you have.
Routes
data-preparation
Use when you need instance images, real-prior image lists, caption files, or concept JSON for training.
Start with sub-skills/data-preparation/SKILL.md.
training
Use when you need diffusers training, SDXL training, prior preservation, modifier tokens, or checkpoint output planning.
Start with sub-skills/training/SKILL.md.
inference
Use when you need to load a Custom Diffusion delta and generate samples from prompts or prompt files.
Start with sub-skills/inference/SKILL.md.
checkpoint-tools
Use when you need delta extraction, compression, or composition.
Start with sub-skills/checkpoint-tools/SKILL.md.
benchmarking
Use when you need to score generated images with CustomConcept101 CLIP/DINO evaluation.
Start with sub-skills/benchmarking/SKILL.md.
Install and runtime notes
- Use Python 3.11 or newer.
- Install a CUDA-enabled PyTorch/torchvision pair before the diffusers workflows.
- Verified public stack:
diffusers==0.21.4, accelerate==0.24.1, transformers==4.31.0, clip-retrieval==2.45.0, pandas, scipy, scikit-learn, tqdm.
- Optional workflow extras:
xformers, bitsandbytes, deepspeed, modelcards.
- The source training, sampling, compression, composition, and evaluation flows are CUDA-backed; the delta extraction route is the only selected CPU-substitutable workflow.
- Legacy checkout-based Stable Diffusion scripts are treated as reference-only or excluded in this generated skill.
Minimal smoke check
After installing the stack, run:
python scripts/check_runtime.py --require-cuda
If you are only checking importability, omit --require-cuda.