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State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers.
Passed 20 of 22 test cases with the skill, and 19 of 22 without it.
2 fixed18 passed either way1 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
I want to generate an image guided by Canny edge boundaries derived from a reference photo. How do I construct the ControlNet model and attach it to a Stable Diffusion pipeline in Python?
| Checked | Without skill | With skill |
|---|---|---|
| Loads ControlNetModel from lllyasviel/control_v11p_sd15_canny | Missed | Passed |
| Initializes StableDiffusionControlNetPipeline with the controlnet instance | Passed | Passed |
The instructions your model reads when the skill loads.
This skill is repo-local and stays inactive until explicitly activated.
When the original instructions refer to legacy tool names, use these Kheish mappings:
terminal => bashweb_extract => web_fetch, plus web_search when discovery is neededsearch_files => grep_search and glob_searchbrowser_* tools require a browser-capable surfaced tool or MCP; if none is available, use the closest available surface and say so explicitlyWhen the instructions mention local helper files, resolve them from ${KHEISH_SKILL_DIR}.
Comprehensive guide to generating images with Stable Diffusion using the HuggingFace Diffusers library.
Use Stable Diffusion when:
Key features:
Use alternatives instead:
test cases passed, vs 19 / 22 without
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