Agent skill · creative production · davila7
stable-diffusion-image-generation
State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.
Why this skill is useful
Provides specific commands and workflows for generating images using Stable Diffusion that the AI wouldn't reliably generate on its own.
What it needs
Requires accelerate, diffusers, torch, transformers installed locally. About 6k tokens when loaded. Last updated 2026-08-06. 30,138 stars on the source repository.
What this skill does
Stable Diffusion Image Generation Comprehensive guide to generating images with Stable Diffusion using the HuggingFace Diffusers library. When to use Stable Diffusion Use Stable Diffusion when: Generating images from text descriptions Performing image-to-image translation (style transfer, enhancement) Inpainting (filling in masked regions) Outpainting (extending images beyond boundaries) Creating variations of existing images Building custom image generation workflows Key features: Text-to-Image: Generate images from natural language prompts Image-to-Image: Transform existing images with text guidance Inpainting: Fill masked regions with context-aware content ControlNet: Add spatial conditioning (edges, poses, depth) LoRA Support: Efficient fine-tuning and style adaptation Multiple Models: SD 1.5, SDXL, SD 3.0, Flux support Use alternatives instead: DALL-E 3: For API-based generation without GPU Midjourney: For artistic, stylized outputs Imagen: For Google Cloud integration Leonardo.ai: For web-based creative workflows Quick start Installation Basic text-to-image Using SDXL (higher quality) Architecture overview Three-pillar design Diffusers is built around three core components: Pipeline inference flow Core concepts Pipelines Pipelines orchestrate complete workflows: Pipeline Purpose ---------- --------- StableDiffusionPipeline Text-to-image (SD 1.x/2.x) StableDiffusionXLPipeline Text-to-image (SDXL) StableDiffusion3Pipeline Text-to-image (SD 3.0) FluxPipeline Text-to-image (Flux models) StableDiffusionImg2ImgPipeline Image-to-image StableDiffusionInpaintPipeline Inpainting Schedulers Schedulers control the denoising process: Scheduler Steps Quality Use Case ----------- ------- --------- ---------- EulerDiscreteScheduler 20-50 Good Default choice EulerAncestralDiscreteScheduler 20-50 Good More variation DPMSolverMultistepScheduler 15-25 Excellent Fast, high quality DDIMScheduler 50-100 Good Deterministic LCMScheduler 4-8 Good Very fast UniPCMultistepScheduler 15-25 …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills davila7/multimodal-stable-diffusion