tao-run-deft-aoi

安装量: 1.2K
排名: #6526

安装

npx skills add https://github.com/nvidia/skills --skill tao-run-deft-aoi

Skill: tao-run-deft-aoi When to Use This Skill Use this skill when the user wants an agent to run the full DEFT AOI improvement loop for an NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection model: baseline evaluation, RCA, synthetic defect generation, data mining, retraining, and deployment gating until a KPI target is met. "Run the DEFT loop" "Fine-tune until FAR below 0.1% at recall=100%" "Improve my AOI ChangeNet model using RCA and synthetic defects" "Iterate training until false accept rate meets the target" Do not use this skill for a single standalone TAO training run, one-off inference, generic anomaly generation, or RCA-only analysis. Use the relevant agent directly when the user asks for only that step. Base Model The loop operates on NVIDIA TAO Visual ChangeNet classify with the NVIDIA C-RADIOv2-B backbone, fine-tuned end-to-end. The architecture is defined in specs/baseline_spec.yaml — that file is the source of truth. All pretrained weights come from HuggingFace ( HF_TOKEN required); NGC_KEY only gates container pulls. ChangeNet backbone resolution + the staged-file/HF-URL fallback for model.backbone.pretrained_backbone_path are owned by references/visual-changenet.md . SigLIP for k-NN mining is owned by references/tao-mine-aoi-images.md . AnomalyGen-side checkpoints (Cosmos-Predict2, T5, NVDINOV2, C-RADIO-V3, DINOv2-large, SAM2, Qwen3-VL — ~22 GB for 2B-only, ~140 GB with 14B + T5-11b) live under /augmentation/anomalygen/base_checkpoints/ ; the paidf-anomalygen container auto-downloads them on first use. The PCB reference dataset under /augmentation/anomalygen/datasets// is also auto-fetchable. See references/paidf-anomalygen.md . Train AutoML Policy Show more Installs 584 Repository nvidia/skills GitHub Stars 1.9K First Seen Jun 8, 2026 Security Audits Gen Agent Trust Hub Pass Socket Pass Snyk Warn

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