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Text-to-image generation, inpainting, and img2img.
Passed 21 of 22 test cases with the skill, and 19 of 22 without it.
2 fixed19 passed either way1 still failing0 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.
To eliminate the performance overhead of dynamic LoRA computation during inference loops, which method merges the adapter directly into the main model weights?
| Checked | Without skill | With skill |
|---|---|---|
| Calls fuse_lora | Missed | Passed |
The instructions your model reads when the skill loads.
Guide to generating images with Stable Diffusion using the HuggingFace Diffusers library.
Use Stable Diffusion when:
Key features:
Use alternatives instead:
pip install diffusers transformers accelerate torch
pip install xformers # Optional: memory-efficient attention
test cases passed, vs 19 / 22 without
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