Installs into .claude/skills of the current project.
Are you the author of Inference?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-inference-0afa5d16)
---
name: inference
description: "Generate images from Custom Diffusion delta checkpoints for SD
1.x-style and SDXL models, including prompt files, compressed deltas, and
pipeline load behavior."
disable-model-invocation: true
metadata:
disco-role: operating
license: NOASSERTION
---
# Inference
Use this sub-skill when you already have a Custom Diffusion delta checkpoint and need image generation.
It covers:
- single-prompt and prompt-file sampling
- compressed and uncompressed delta checkpoints
- SD 1.x-style and SDXL sampling paths
- output naming and sample-layout expectations
It does not cover training or delta math. Route those tasks to [`../training/SKILL.md`](../training/SKILL.md) and [`../checkpoint-tools/SKILL.md`](../checkpoint-tools/SKILL.md).
## Start here
1. Read [`references/api-reference.md`](references/api-reference.md).
2. Read [`references/workflows.md`](references/workflows.md).
3. Run [`../checkpoint-tools/scripts/check_delta_layout.py`](../checkpoint-tools/scripts/check_delta_layout.py) before a long sampling run.
4. Check [`references/troubleshooting.md`](references/troubleshooting.md) when the delta layout, model cache, or prompt file is wrong.
## Runtime notes
- The source sampler uses CUDA, a fixed seed, 200 inference steps, and guidance scale 6.
- A compressed delta needs the matching compression flag or a layout checker will flag the `u` / `v` payload.
- The SDXL path uses the XL pipeline and the dual-text-encoder load behavior described in the API reference.
