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AI & LLM Engineering · NVIDIA AI Platform
Skills
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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 145 | 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/ | 3.6k | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 146 | 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/ | 3.6k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 147 | 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/ | 3.6k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 148 | 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/ | 3.6k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 149 | CLIP vision-language model for image-text retrieval, zero-shot classification, embedding extraction, ONNX export, and TensorRT deployment. | NVIDIA/ | 3.6k | — | ~4k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 150 | 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/ | 3.6k | — | ~4.9k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 151 | NV-Tesseract AD Diffusion — diffusion-based anomaly detection and fine-tuning for multivariate time series. | NVIDIA/ | 3.6k | — | ~2.9k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 152 | NV-Tesseract Forecasting — transformer-based multivariate time series forecasting with DARR (context-enhanced kNN retrieval), interpretability, and fine-tuning. | NVIDIA/ | 3.6k | — | ~3.2k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 153 | InternVideo2-CLIP L14 (TAO videoclip) for video-text retrieval, zero-shot classification, embedding extraction, LoRA fine-tuning, ONNX export, and TensorRT deployment. | NVIDIA/ | 3.6k | — | ~3.5k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 154 | BEVFusion for multi-sensor 3D object detection. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~3.4k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 155 | Co-DETR (CoDINO) for object detection. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~4.8k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 156 | DINO (DETR with Improved DeNoising Anchor Boxes) for 2D object detection. | NVIDIA/ | 3.6k | — | ~2.8k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 157 | Grounding DINO for open-set object detection. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~3.9k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 158 | PyTorch-based TAO image classification. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~3.6k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 159 | Masked Auto-Encoder (MAE) for self-supervised pretraining and fine-tuning. | NVIDIA/ | 3.6k | — | ~2.9k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 160 | Mask Grounding DINO for grounded instance segmentation. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~3.5k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 161 | Mask2Former for universal image segmentation (panoptic, instance, and semantic). | NVIDIA/ | 3.6k | — | ~5k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 162 | Metric-learning recognition (ml-recog) for fine-grained visual recognition. | NVIDIA/ | 3.6k | — | ~2.9k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 163 | NVDINOv2 for self-supervised visual representation learning. | NVIDIA/ | 3.6k | — | ~3.1k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 164 | OneFormer for universal image segmentation. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~5k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 165 | PointPillars for 3D object detection from LiDAR point clouds. | NVIDIA/ | 3.6k | — | ~4k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 166 | RT-DETR (Real-Time DEtection TRansformer) for 2D object detection. | NVIDIA/ | 3.6k | — | ~4.5k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 167 | SegFormer for semantic segmentation. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~3.7k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 168 | A skill your agent uses when deploying, operating, or integrating the VSS 3.2 GA RT-Embed Video Embedding microservice. | NVIDIA/ | 3.6k | — | ~3.7k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 169 | Runs NVIDIA garak probe suites (jailbreak, prompt injection, data leakage, toxicity, and more) against an LLM endpoint - Hugging Face models, OpenAI-compatible APIs, or Bedrock - then interprets the… | mukul975/ | 34k | — | ~2.9k | Automated safety check: Warn | Apache-2.0 | 1 mo ago |
| 170 | Deploys Llama Guard 3 safety classification, NeMo Guardrails programmable dialogue rails, and LLM Guard input/output scanner pipelines as complementary runtime defenses that inspect and constrain… | mukul975/ | 34k | — | ~3.1k | Automated safety check: Warn | Apache-2.0 | 1 mo ago |
| 171 | Triage a dead or degraded GPU on a CoreWeave node fast — decide reschedule vs GPU-reset vs node-reboot vs RMA from an Xid code or a pasted dmesg / nvidia-smi blob, so a bad card does not silently… | jeremylongshore/ | 2.8k | — | ~3.2k | Automated safety check: Pass | MIT | yesterday |
| 172 | Cross-engine decision rubric for self-hosting or recommending an LLM serving stack. | agentsope/ | 436 | — | ~6.1k | Automated safety check: Pass | MIT | 2 days ago |
| 173 | 173.Agentsop Vllm Decision SOP for serving LLMs with vLLM. An agent skill from agentsope/SkillAlchemy. | agentsope/ | 436 | — | ~6.1k | Automated safety check: Pass | MIT | 2 days ago |
| 174 | 174.Engine Sglang Serve a Hugging Face model with SGLang on a Linux machine with an NVIDIA or AMD GPU, configured from the model's SGLang cookbook page — or, when it has none, from the model's own files — and join it… | autonomous-ai/ | 1.2k | — | ~1.5k | Automated safety check: Pass | MIT | yesterday |
| 175 | 175.Engine Vllm Serve a Hugging Face model with vLLM on a Linux machine with an NVIDIA or AMD GPU, configured from the model's official vLLM recipe — or, when it has none, from the model's own files — and join it… | autonomous-ai/ | 1.2k | — | ~1.9k | Automated safety check: Pass | MIT | yesterday |
| 176 | Diagnose Day-2 AKS GPU and KAITO incidents using profile-aware, read-only evidence. | microsoft/ | 255 | — | ~764 | Automated safety check: Pass | MIT | yesterday |
| 177 | A skill your agent uses for hands-on DOCA GPI programming — wiring a GPU-Packet-Initiator context so a CUDA kernel drives RDMA queues directly from GPU memory without host CPU mediation. | NVIDIA/ | 3.6k | — | ~3.9k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 178 | A skill your agent uses when the user is doing hands-on DOCA GPUNetIO programming — wiring a CUDA kernel on an NVIDIA GPU to a doca-eth queue via docagpuethrxq / docagpuethtxq, standing up the… | NVIDIA/ | 3.6k | — | ~3.7k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 179 | A skill your agent uses when the user is building, running, or interpreting the doca/tools/gpunetioibwritebw client+server benchmark — a CUDA kernel on the client posts RDMA WRITE work requests… | NVIDIA/ | 3.6k | — | ~4.2k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 180 | Install Holoscan SDK v4.3+ via Conda in a CUDA 13 environment. | NVIDIA/ | 3.6k | — | ~2k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 181 | Install Holoscan SDK natively on Ubuntu via apt. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~1.6k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 182 | Install Holoscan SDK Python wheel via pip into a venv. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~1.6k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 183 | A skill your agent uses when you need to add, remove, edit, list, or change the boot default of an nvfancontrol fan profile on a Jetson/Tegra (Orin, Thor) target. | NVIDIA/ | 3.6k | — | ~4.3k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 184 | Enable Jetson Thor 25G/10G/1G MGBE QSFP via kernel-DT overlay. | NVIDIA/ | 3.6k | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 185 | A skill your agent uses when you need to add, remove, edit, list, or change the boot default of an nvpmodel power mode on a Jetson/Tegra (Orin, Thor) target. | NVIDIA/ | 3.6k | — | ~4.4k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 186 | Download NVIDIA Jetson Linux BSP artifacts (BSP tarball, sample rootfs, publicsources, x-tools, guides) for the active target. | NVIDIA/ | 3.6k | — | ~3k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 187 | Reclaim DRAM by disabling unused subsystems across MB1 BCT, MB2 BCT, kernel reserved-memory, and SWIOTLB. | NVIDIA/ | 3.6k | — | ~2k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 188 | A skill your agent uses when you need to print Jetson BSP info (L4T version, board configs, rootfs state) from a LinuxforTegra root on the host PC. | NVIDIA/ | 3.6k | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 189 | A skill your agent uses when integrating NVIDIA NeMo Fabric into a consumer application, service, evaluation harness, or platform through the typed Python SDK — translating the consumer's own… | NVIDIA/ | 3.6k | — | ~5.8k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 190 | Validate and use selective and full activation recompute in Megatron Bridge to reduce GPU memory usage at the cost of extra compute. | NVIDIA/ | 3.6k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 191 | Orchestration skill for NVIDIA Nemotron Speech (Riva) / NeMo ASR domain and language adaptation. | NVIDIA/ | 3.6k | — | ~3k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 192 | Used for running NV-Segment-CT VISTA3D on CT NIfTI volumes and recording label-map evidence. | NVIDIA/ | 3.6k | — | ~2.1k | Automated safety check: Notes | Apache-2.0 | 2 days ago |