tao-finetune-huggingface-model
About
Fine-tune any HuggingFace CV / VLM / LLM model on local NVIDIA GPUs inside an NGC PyTorch container when no dedicated TAO model skill matches. Use when the user wants to fine-tune a HuggingFace model (full or LoRA), train a vision / VLM / LLM model end-to-end, generate a reproducible HF training pipeline, smoke-test a HuggingFace model locally before scale-up, push a fine-tuned model to the HF Hub with a model card, or emit a self-contained rerun skill for an existing HuggingFace finetune. Supports image classification, object detection, semantic / instance / panoptic segmentation, depth estimation, image-text-to-text VLM (SFT / LoRA), and LLM SFT / DPO / GRPO. Six-step workflow: inspect and qualify, hardware and NGC image, research, generate and smoke, train + eval + infer, push and emit rerun skill. Do not use for any Hugging Face model ID claimed by a dedicated `skills/models/*` skill; the model skill and its declared execution environment take precedence.
Capabilities
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Provenance
- Discovered
- Relayed by agntcy
- Identifier
- urn:air:outshift.io:agntcy:tao-finetune-huggingface-model
- Catalog host
- outshift.io · via agntcy registry
- Anchor check
- Not anchored
- Last crawled
- seen 1h ago
Discovered through outshift.io's registry, not anchored by StealthStack. We relay the listing as-is; we have not checked that the URN authority matches the publishing host. How trust works →