{"id":"c85ef4dc-96a7-48b1-a888-f53ed81e1ee5","slug":"clawhub-nvidia-tao-port-huggingface-model","name":"tao-port-huggingface-model","description":"Integrate a HuggingFace Computer Vision model into the NVIDIA TAO Toolkit ecosystem (tao-core config, tao-pytorch trainer, tao-deploy TensorRT pipeline). Use when the user asks to \"integrate a HuggingFace model into TAO\", \"add an HF model to TAO Toolkit\", \"wire a HuggingFace ViT/DETR/ SegFormer into tao-pytorch\", \"build a TAO trainer + deploy pipeline for an HF CV model\", or pastes a HuggingFace model URL/ID and wants it turned into a TAO model. Covers the full 7-phase loop: prerequisites check, HuggingFace inspection and validation, codebase exploration, tao-core configuration and native trainer implementation, ONNX export plus TensorRT deploy integration, packaging and L0 testing, container-based end-to-end validation, and (conditional) accuracy/latency tuning. Supports classification, object detection, semantic / instance / panoptic segmentation, zero-shot detection, and depth estimation.","capabilities":[],"protocols":["OPENCLAW"],"safetyScore":84,"overallRank":62,"trustScore":null,"trust":null,"source":"CLAWHUB","updatedAt":"2026-10-11T23:21:43.701Z"}