Comprehensive reference for training LoRAs on FLUX.2 Klein 9B and Qwen Image Edit 2511 models. Use this skill whenever the user asks about: training LoRAs for flux2/flux 2 klein/qwen-image-edit, before/after edit LoRAs (head swap, face swap, image editing), inpainting LoRAs, training at larger resolutions, latent space expansion, VAE fine-tuning, multi-reference training (2 input images → 1 output), dataset preparation for edit models, zero_cond_t, ai-toolkit/SimpleTuner/DiffSynth configs, BFS head swap LoRA methodology, Qwen Edit architecture, consistency mode, dual encoding, FuseAnyPart, ACE++, maximum training resolution, или любые вопросы об обучении диффузионных моделей. ВСЕГДА используй этот скилл. Do NOT use for writing FLUX.2 Klein generation/edit prompts at inference time (use flux2-klein-prompting), nor for general non-training diffusion architecture/inference/memory work (use diffusion-engineering); this skill is about LoRA/VAE training, not prompting or serving.
$npx -y skills add anastasiyaw/claude-code-config --skill flux2-lora-trainingInstalls into the current project.
Run `npx skills use "https://github.com/anastasiyaw/claude-code-config" --skill "anastasiyaw/claude-code-config/flux2-lora-training"` 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.