tao-finetune-huggingface-model

Local NVIDIA GPU fine-tuning for HuggingFace models, grounded in live-fetched documentation with curated references as a fallback safety net. One NGC container, a few focused scripts, one push to HF Hub. Follow the rules in this file; don't improvise.

Order of authority (highest first):

1. User input — explicit model_id, dataset_id, training_method, config.yaml overrides.
2. Live research — model card, HF repo example, author finetune script, HF task docs, paper; always fetched (Step 3 + references/research-priorities.md).
3. Curated references (references/*.md) — fallback when live research is silent/ambiguous.
4. Your training-data memory — last resort; suspect, cross-check against (2)/(3).

Conflict resolution between (2) and (3) and the source-line discrepancy note are in references/research-priorities.md.