
This wraps HuggingFace's Diffusers library for running Stable Diffusion locally, which means you need GPU access but get full control over the generation…
$ npx -y skills add orchestra-research/ai-research-skills --skill stable-diffusion-image-generation --agent claude-codeInstalls into .claude/skills of the current project.
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This wraps HuggingFace's Diffusers library for running Stable Diffusion locally, which means you need GPU access but get full control over the generation pipeline. It covers text-to-image, img2img, inpainting, and ControlNet for spatial conditioning like edge maps or pose skeletons. The documentation includes scheduler comparisons (DPMSolver gets you quality in 15-25 steps instead of 50) and walks through SDXL and LoRA adapters. Use this when you want to generate images programmatically without API costs or need fine-grained control over the diffusion process. If you just need images and don't want to manage GPU inference, stick with DALL-E 3 or Midjourney instead.
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