Lora Finetune

This skill appears coherent for local LoRA fine-tuning. Things to consider before installing/running: - HF_TOKEN: provide a Hugging Face token scoped appropriately (prefer read-only if possible). The token is used to download models from the Hub. - Dependencies: you must install torch, diffusers, peft, and PIL (and any Apple Silicon-specific builds) yourself; the skill does not include an automated installer. - LLM scoring mismatch: the README mentions an "LLM-as-judge" evaluation, but the provided scripts do not perform any LLM calls — if you expect automated scoring, you will need additional code or instructions. - Model provenance & licensing: verify the model IDs (e.g., FLUX.1-schnell, stable-diffusion-v1-5) and their licenses before downloading or fine-tuning, especially if you will redistribute results. - Resource use: training may be memory- and time-intensive; test with small steps and small datasets first and monitor MPS/CPU memory. - Safety: the scripts operate on local files only and save outputs locally, but always inspect third-party model IDs and avoid supplying sensitive data in training captions. Overall, the skill looks internally consistent and appropriate for its stated purpose, with moderate non-security caveats about missing LLM scoring and explicit dependency installation instructions.