---

name: local-inference description: "Routes InfiniteYou-FLUX self-contained identity-preserving image generation through the bundled runtime helper, model variants, control images, LoRA options, and CUDA memory settings." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Local Inference

Use this sub-skill when a task asks how to run, adapt, debug, or validate local InfiniteYou-FLUX image generation from an identity image and text prompt. The bundled helper uses this skill's runtime/pipelines/ implementation by default, so normal generation does not require the original repository checkout.

Read first

• references/workflows.md for common identity, control-image, model-variant, LoRA, and low-memory recipes.
• references/cli-reference.md for the generated helper flags and the official CLI surface it mirrors.
• references/api-reference.md for verified InfUFluxPipeline signatures and parameter semantics.
• references/troubleshooting.md for face, CUDA, model-access, LoRA, prompt, and output failures.
• scripts/run_infinite_you_flux.py when you need a bundled dry-run, preflight, or generation entry point.

Use this route for

• Building a local generation command from an identity image, prompt, optional control image, seed, size, and output directory.
• Choosing between aes_stage2 and sim_stage1 model variants.
• Deciding whether to enable --cpu-offload, --quantize-8bit, or both to reduce peak VRAM.
• Using optional Realism or Anti-blur LoRA files when the local model tree contains them.
• Calling the bundled Python API directly through InfUFluxPipeline.
• Preflighting images, bundled runtime imports, CUDA availability, and local model paths before a heavy run.

Fast workflow

1. Check setup and model access in the root installation and models reference. Full generation requires CUDA and model files/access; --cpu-offload is not CPU-only execution.
2. Run a no-side-effect plan first:

   python scripts/run_infinite_you_flux.py --dry-run \
     --id-image path/to/id.jpg \
     --prompt "A person, portrait, cinematic" \
     --model-dir models/InfiniteYou \
     --base-model-path models/FLUX.1-dev \
     --cpu-offload --quantize-8bit
   

3. Run a preflight check before generation:

   python scripts/run_infinite_you_flux.py --check-only \
     --id-image path/to/id.jpg \
     --prompt "A person, portrait, cinematic" \
     --model-dir models/InfiniteYou \
     --base-model-path models/FLUX.1-dev
   

4. If preflight passes and CUDA/model access is available, run without --dry-run or --check-only.
5. Confirm a PNG was written and record the seed from the output filename or terminal output.

Route elsewhere

• For model directory layout, Hugging Face access, demo model switching, or Gradio launch questions, read ../demo-and-model-setup/SKILL.md.
• For modifying face detection, Resampler, InfuseNet injection, offload internals, or Diffusers integration, read ../pipeline-internals/SKILL.md.
• For code/model license and responsible-use constraints, read ../../references/safety-and-licenses.md.

Acceptance checks

A good local-inference answer should name the exact generation inputs, model variant, CUDA/memory strategy, model path/access assumptions, whether downloads are allowed, and validation signal. It should avoid telling the user to open or run source-repo scripts directly; use the bundled helper or describe an equivalent API call against the bundled runtime.