# Stable Diffusion XL Pipeline

> Orchestrates SDXL image generation via the Stability AI REST API with ControlNet conditioning, IP-Adapter style transfer, and automatic prompt enhancement using CLIP interrogation.

- Skill: `agentskillexchange/stable-diffusion-xl-pipeline` (Agent Skill)
- Install (CLI): `npx skillmds@latest add agentskillexchange/stable-diffusion-xl-pipeline`
- Raw SKILL.md: https://api.skillmd.com/api/skills/agentskillexchange/stable-diffusion-xl-pipeline/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: agentskillexchange (https://skillmd.com/u/agentskillexchange)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/agentskillexchange/stable-diffusion-xl-pipeline

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# Stable Diffusion XL Pipeline

Orchestrates SDXL image generation via the Stability AI REST API with ControlNet conditioning, IP-Adapter style transfer, and automatic prompt enhancement using CLIP interrogation.

## Installation

Use the upstream install or setup path that matches your environment:
- git clone https://github.com/Stability-AI/generative-models.git
- pip install hatch
- pip install "numpy>=1.17" "PyWavelets>=1.1.1" "opencv-python>=4.1.0.25"
- pip install --no-deps invisible-watermark

Requirements and caveats from upstream:
- python scripts/sampling/simple_video_sample_4d2.py --input_path assets/sv4d_videos/camel.gif --output_folder outputs (after downloading [sv4d2.safetensors](https://huggingface.co/stabilityai/sv4d2.0) from HuggingFace...
- Run inference: python scripts/sampling/simple_video_sample_4d2.py --input_path <path/to/video>
- Run inference: python scripts/sampling/simple_video_sample_4d2.py --model_path checkpoints/sv4d2_8views.safetensors --input_path assets/sv4d_videos/chest.gif --output_folder outputs

Basic usage or getting-started notes:
- To run **SV4D 2.0** on a single input video of 21 frames:
- **Low VRAM environment** : To run on GPUs with low VRAM, try setting --encoding_t=1 (of frames encoded at a time) and --decoding_t=1 (of frames decoded at a time) or lower video resolution like --img_size=512.
- The 5x8 model takes 5 frames of input at a time. But the inference scripts for both model take 21-frame video as input by default (same as SV3D and SV4D), we run the model autoregressively until we generate 21 frames.

- Source: https://github.com/Stability-AI/generative-models
- Extracted from upstream docs: https://raw.githubusercontent.com/Stability-AI/generative-models/HEAD/README.md

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/stable-diffusion-xl-pipeline/)