diffusion-engineering
byanastasiyaw· 37 skills
Практическая инженерия диффузионных моделей: архитектуры, обучение, инференс, оптимизация памяти. Использовать при любых задачах с диффузионными моделями: проектирование или модификация архитектуры (UNet/DiT/Flow/Flux), выбор и настройка schedulers/samplers, дообучение (LoRA/DreamBooth/full fine-tune), оптимизация памяти (AMP/checkpointing/ZeRO/FSDP/quantization), замена или fusion текст-энкодеров (CLIP/Qwen), работа с Diffusers, отладка диффузионных пайплайнов, оценка качества (FID/CLIPScore/LPIPS), latent diffusion, VAE, guidance/CFG, rectified flow, Stable Diffusion, SDXL, Flux. Также применять при вопросах про GPU-память при обучении генеративных моделей, text-to-image пайплайны, ControlNet, multi-encoder fusion, WebDataset. Do NOT use for writing FLUX.2 Klein generation prompts (use flux2-klein-prompting) или для FLUX.2 Klein / Qwen-Edit LoRA-тренинга и edit-LoRA (use flux2-lora-training); это общая диффузионная инженерия, не специфика FLUX.2 Klein.
How to install diffusion-engineering?
anastasiyaw/claude-code-config/diffusion-engineering
$npx -y skills add anastasiyaw/claude-code-config --skill diffusion-engineeringInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/anastasiyaw/claude-code-config" --skill "anastasiyaw/claude-code-config/diffusion-engineering"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/anastasiyaw/claude-code-config" that are relevant to the current task. Run `npx skills add "https://github.com/anastasiyaw/claude-code-config"` and select the relevant skills, then follow their instructions.
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