AI model or service
NVIDIA AI Platform agent skills, page 4
NVIDIA AI Platform skills, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 145 | Used for generating synthetic body MRI volumes with NV-Generate-CTMR rflow-mr. | NVIDIA/ | 3.5k | — | ~2k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 146 | A skill your agent uses for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. | NVIDIA/ | 3.5k | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 147 | A skill your agent uses when operating PAIDF Curation and Retrieval or NVIDIA Cosmos Curator pipelines (split, filter, caption, embed, dedup, shard, image annotate) or PAIDF Data Mining… | NVIDIA/ | 3.5k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 148 | Router for NVIDIA NuRec/NRE: USDZ rendering, NCore conversion, 3DGS, gRPC sensor sim, carline adaptation, PhysicalAI HF datasets. | NVIDIA/ | 3.5k | — | ~4.5k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 149 | Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse… | NVIDIA/ | 3.5k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 150 | Official NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and… | NVIDIA/ | 3.5k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 151 | A skill your agent uses when a user asks to build, optimize, backtest, rebalance, or analyze a stock portfolio with Mean-CVaR, Mean-Variance/SOCP variance caps, efficient frontiers, scenario… | NVIDIA/ | 3.5k | — | ~4.9k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 152 | Performs deep Root Cause Analysis (RCA) on NVIDIA TAO Visual ChangeNet classification experiments with image-evidence-driven investigation. | NVIDIA/ | 3.5k | — | ~1.6k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 153 | Performs gap analysis on NVIDIA TAO VCN Classify (Visual Component Net) experiments by invoking the pinned TAO data-services container directly via docker run … gapanalysis vcnaoi … — picks the… | NVIDIA/ | 3.5k | — | ~4.3k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 154 | CLIP vision-language model for image-text retrieval, zero-shot classification, embedding extraction, ONNX export, and TensorRT deployment. | NVIDIA/ | 3.5k | — | ~4k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 155 | Fine-tune any HuggingFace CV / VLM / LLM model on local NVIDIA GPUs inside an NGC PyTorch container when no dedicated TAO model skill matches. | NVIDIA/ | 3.5k | — | ~4.9k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 156 | NV-Tesseract AD Diffusion — diffusion-based anomaly detection and fine-tuning for multivariate time series. | NVIDIA/ | 3.5k | — | ~2.9k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 157 | NV-Tesseract Forecasting — transformer-based multivariate time series forecasting with DARR (context-enhanced kNN retrieval), interpretability, and fine-tuning. | NVIDIA/ | 3.5k | — | ~3.2k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 158 | InternVideo2-CLIP L14 (TAO videoclip) for video-text retrieval, zero-shot classification, embedding extraction, LoRA fine-tuning, ONNX export, and TensorRT deployment. | NVIDIA/ | 3.5k | — | ~3.5k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 159 | Multi-step video annotation pipeline that turns raw videos into Chain-of-Thought training data — multi-level captions, structured descriptions, and QA pairs (MCQ, binary, open-ended) with reasoning… | NVIDIA/ | 3.5k | — | ~2.8k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 160 | The mandatory pre-launch gate and four-verb execution contract for every TAO workflow or action. | NVIDIA/ | 3.5k | — | ~4.5k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 161 | Run the canonical NVIDIA AOI three-phase training pipeline — Phase 1 AutoML baseline (HPO), Phase 2 DEFT loop (RCA → SDG → mining → plain-train retrain), Phase 3 AutoML refinement on the… | NVIDIA/ | 3.5k | — | ~4.3k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 162 | Run the full DEFT AOI improvement loop for NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection models: baseline evaluate, RCA, Cosmos AnomalyGen / AMP synthetic defects, k-NN mining, retraining… | NVIDIA/ | 3.5k | — | ~5k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 163 | BEVFusion for multi-sensor 3D object detection. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~3.4k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 164 | CenterPose for keypoint / pose estimation. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~2.9k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 165 | Monocular depth estimation using Metric Depth Anything v2 or Relative Depth Anything architectures. | NVIDIA/ | 3.5k | — | ~3.9k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 166 | DINO (DETR with Improved DeNoising Anchor Boxes) for 2D object detection. | NVIDIA/ | 3.5k | — | ~2.8k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 167 | Real-time stereo depth estimation using FastFoundationStereo (FFS), the distilled bp2 commercial variant of FoundationStereo. | NVIDIA/ | 3.5k | — | ~3k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 168 | Stereo depth estimation using FoundationStereo. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~3.2k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 169 | Grounding DINO for open-set object detection. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~3.9k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 170 | PyTorch-based TAO image classification. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~3.6k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 171 | Masked Auto-Encoder (MAE) for self-supervised pretraining and fine-tuning. | NVIDIA/ | 3.5k | — | ~2.9k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 172 | Mask Grounding DINO for grounded instance segmentation. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~3.5k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 173 | Mask2Former for universal image segmentation (panoptic, instance, and semantic). | NVIDIA/ | 3.5k | — | ~5k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 174 | Metric-learning recognition (ml-recog) for fine-grained visual recognition. | NVIDIA/ | 3.5k | — | ~2.9k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 175 | NVDINOv2 for self-supervised visual representation learning. | NVIDIA/ | 3.5k | — | ~3.1k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 176 | OCDNet for scene text detection. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~3.6k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 177 | OCRNet for scene text recognition. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~4.4k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 178 | OneFormer for universal image segmentation. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~5k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 179 | PointPillars for 3D object detection from LiDAR point clouds. | NVIDIA/ | 3.5k | — | ~4k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 180 | Pose classification using ST-GCN (Spatial Temporal Graph Convolutional Network). | NVIDIA/ | 3.5k | — | ~3.8k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 181 | RT-DETR (Real-Time DEtection TRansformer) for 2D object detection. | NVIDIA/ | 3.5k | — | ~4.5k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 182 | SegFormer for semantic segmentation. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~3.7k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 183 | A skill your agent uses when deploying, operating, or integrating the VSS 3.2 GA RT-Embed Video Embedding microservice. | NVIDIA/ | 3.5k | — | ~3.7k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 184 | A skill your agent uses to call the VIOS REST API (sensor list, timelines, clip extraction, snapshots, add/delete sensors and streams). | NVIDIA/ | 3.5k | — | ~5k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 185 | A skill your agent uses to run top-level VSS fusion search on archived video, or to ingest video files / RTSP streams for search. | NVIDIA/ | 3.5k | — | ~4.2k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 186 | cuOpt REST server — start server, endpoints, Python/curl client examples. | NVIDIA/ | 3.5k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 187 | Prepare and run PAIDF Cosmos Predict video generation for DEFT media samples. | NVIDIA/ | 3.5k | — | ~4.6k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 188 | Create and push a signed, annotated NeMo Relay beta tag from its release branch or validated main. | NVIDIA/ | 192 | — | ~728 | Automated safety check: Pass | Apache-2.0 | today |
| 189 | Create and push a signed, annotated NeMo Relay release-candidate tag from its validated release branch. | NVIDIA/ | 192 | — | ~635 | Automated safety check: Pass | Apache-2.0 | today |
| 190 | Create and push a signed, annotated NeMo Relay stable tag, then prepare an unpublished GitHub Release draft for review. | NVIDIA/ | 192 | — | ~827 | Automated safety check: Pass | Apache-2.0 | today |
| 191 | Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. | NVIDIA/ | 3.5k | — | ~3.9k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 192 | LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.5k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | yesterday |