ultra-ml-intern

Use when the user names a specific ML model (e.g. DINOv3, SAM 2, Whisper, Qwen2-VL) and wants its real/official code, training recipe, or papers found, verified, or archived locally for grounded coding. Triggers include "find the real code for this model", "harvest DINOv3", "store the model's code and papers locally", "archive the training/inference code", "set up a local source-of-truth / reference archive for a model", or any request that future coding against a model be grounded in its actual source instead of training-time memory.

Use when the user asks to fine-tune, train, evaluate, audit, or ship a machine-learning model on the Hugging Face ecosystem — SFT, DPO, GRPO, RLHF, LoRA/QLoRA, post-training, dataset auditing, paper-driven research, hf jobs submission, Trackio monitoring, push-to-Hub. Triggers include "fine-tune", "train a model", "SFT", "DPO", "GRPO", "RLHF", "post-training", "audit this dataset", "literature review for X task", "submit hf job", "find a dataset for X", "best recipe for X", "hyperparameter sweep", "OOM during training", "push to Hub". Replicates the workflow of huggingface/ml-intern inside Claude Code with zero new dependencies.