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AI & LLM Engineering · CUDA · By NVIDIA
Skills
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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Shows how to launch distributed Megatron-LM training on a SLURM cluster: sbatch skeleton, torch.distributed.run setup, CUDA_DEVICE_MAX_CONNECTIONS rules and failure diagnosis. | NVIDIA/ | 18k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | today |
| 2 | Diagnose and fix Cosmos3 environment, installation, and runtime errors. | NVIDIA/ | 560 | — | ~1.3k | Automated safety check: Notes | Unknown | yesterday |
| 3 | A skill your agent uses when something is wrong: Search() hangs, all evaluations return INVALIDSCORE, scores aren't improving, every config returns the same number, ptxas errors fill the log, CV% is… | NVIDIA/ | 138 | — | ~2.9k | Automated safety check: Notes | Apache-2.0 | 18 days ago |
| 4 | Guide users through Cosmos3 supervised fine-tuning (SFT) post-training: preparing the example dataset and Wan2.2 VAE, converting the base checkpoint to DCP, launching distributed training (paired… | NVIDIA/ | 560 | — | ~2.7k | Automated safety check: Pass | Unknown | yesterday |
| 5 | A skill your agent uses when composing the Search(...) call and calling .start(). | NVIDIA/ | 138 | — | ~2.2k | Automated safety check: Notes | Apache-2.0 | 18 days ago |
| 6 | Turns a parquet of image file paths into a parquet of embeddings with CLIP, SigLIP or a TAO checkpoint, using the TAO Data Services container, ahead of neighbor mining. | NVIDIA/ | 3.6k | — | ~2k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 7 | Measure Jetson DRAM/NvMap usage and verify before/after memory reclamation with live audit data. | NVIDIA/ | 3.6k | 1 repo | ~2.3k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 8 | Pick Jetson-compatible containers, vLLM runtime images, and Jetson AI Lab PyPI indexes; maps Orin SM 8.7 vs Thor SM 11.0 and JetPack-specific package choices. | NVIDIA/ | 3.6k | 1 repo | ~1.8k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 9 | Continue KERMT pretraining on a custom SMILES corpus with a groverbase, cmim, or hybrid checkpoint. | NVIDIA/ | 3.6k | 1 repo | ~4.1k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 10 | Extract per-molecule embeddings from any encoder-bearing KERMT checkpoint. | NVIDIA/ | 3.6k | 1 repo | ~1.9k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 11 | Finetune a pretrained KERMT encoder on a labeled CSV. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | 1 repo | ~4.1k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 12 | A skill your agent uses when writing or debugging nvMolKit Python code for GPU-accelerated RDKit fingerprints, similarity, conformers, clustering, and molecular searches. | NVIDIA/ | 3.6k | 1 repo | ~4.8k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 13 | Evaluate whether an existing hot path is a credible NVIDIA Warp candidate. | NVIDIA/ | 3.6k | — | ~4.9k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 14 | A skill your agent uses when training, evaluating, or exporting Workflow policies with online RSL-RL or RLinf, including RL checkpoint and Workflow handoff. | NVIDIA/ | 3.6k | 1 repo | ~3.8k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 15 | Pretrain a fresh KERMT model from scratch on a user-provided corpus. | NVIDIA/ | 3.6k | 1 repo | ~2.4k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 16 | A skill your agent uses when compile time or startup time is the problem in code that uses Warp: a request to improve, optimize, or cut compile times; an app that is slow to start or stalls at the… | NVIDIA/ | 3.6k | — | ~3.5k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 17 | A skill your agent uses when installing, repairing, reusing, inspecting, or verifying readiness of the native NVIDIA Video Codec SDK or PyNvVideoCodec on Jetson, including the one-frame… | NVIDIA/ | 3.6k | 1 repo | ~2.4k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 18 | DALI imperative dynamic mode (nvidia.dali.experimental.dynamic, ndd): use when working on ndd code or migrating pipelines; skip pipeline-only tasks. | NVIDIA/ | 3.6k | — | ~3.7k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 19 | A skill your agent uses for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance. | NVIDIA/ | 3.6k | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 20 | Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). | NVIDIA/ | 3.6k | — | ~3.2k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 21 | NVIDIA DeepStream SDK development with Python pyservicemaker API. | NVIDIA/ | 3.6k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 22 | Build deterministic forecast scripts with Earth2Studio (model, data source, IO, inference). | NVIDIA/ | 3.6k | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 23 | Install or repair the FoundationPose perception pipeline and build its FoundationStereo TensorRT engines. | NVIDIA/ | 3.6k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 24 | Used for generating synthetic body MRI volumes with NV-Generate-CTMR rflow-mr. | NVIDIA/ | 3.6k | — | ~2k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 25 | 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 |
| 26 | 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 |
| 27 | 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 |
| 28 | A skill your agent uses when the operator is authoring, building, loading, or debugging a custom doca-bench plug-in — a versioned shared library with DOCAEXPERIMENTAL-marked C entry points that… | NVIDIA/ | 3.6k | — | ~4k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 29 | 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 |
| 30 | 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 |
| 31 | 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 |
| 32 | A skill your agent uses when the user is measuring GPU-kernel-initiated RDMA WRITE latency through doca-gpunetio — building and running the gpunetioibwritelat client + server pair under… | NVIDIA/ | 3.6k | — | ~3.8k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 33 | Guide installing Earth2Studio via uv or pip, selecting model extras, and configuring the environment. | NVIDIA/ | 3.6k | — | ~1.6k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 34 | 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 |
| 35 | 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 |
| 36 | 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 |
| 37 | 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 |
| 38 | Used for command-shape or live NV-Reason-CXR chest X-ray reasoning smoke tests. | NVIDIA/ | 3.6k | — | ~3.9k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 39 | 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 |
| 40 | Used for running NV-Segment-CTMR on CT or MRI NIfTI volumes and recording label-map evidence. | NVIDIA/ | 3.6k | — | ~2.3k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 41 | Create, refine, or fix NVIDIA voice agents (Cascaded or Omni) with Pipecat or LiveKit. | NVIDIA/ | 3.6k | — | ~844 | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 42 | NVIDIA RAG Blueprint — deploy, configure, troubleshoot, and manage. | NVIDIA/ | 3.6k | — | ~2.8k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 43 | How to swap the DeepStream CV detection model in the VSS Alerts Blueprint verification (2dcv) mode - covers ONNX export, custom bbox parsers, compose mount gotchas, nvinfer config, runtime TRT… | NVIDIA/ | 3.6k | — | ~4.5k | Automated safety check: Notes | Apache-2.0 | 2 days ago |
| 44 | Validate and use CPU offloading in Megatron Bridge, including layer-level activation offloading and fractional optimizer state offloading with HybridDeviceOptimizer. | NVIDIA/ | 3.6k | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 45 | Validate and use CUDA graph capture in Megatron Bridge, including local full-iteration graphs and Transformer Engine scoped graphs for attention, MLP, and MoE modules. | NVIDIA/ | 3.6k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 46 | Validate and use MoE expert-parallel communication overlap in Megatron-Bridge, including overlapmoeexpertparallelcomm, delaywgradcompute, and flex dispatcher backends such as DeepEP and HybridEP. | NVIDIA/ | 3.6k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 47 | Operational guide for enabling Megatron FSDP in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification. | NVIDIA/ | 3.6k | — | ~973 | Automated safety check: Pass | Apache-2.0 | 2 days ago |
| 48 | Techniques for reducing peak GPU memory in Megatron Bridge — expandable segments, PEFT + SP input re-gather, parallelism resizing, activation recompute, CPU offloading constraints, and common OOM… | NVIDIA/ | 3.6k | — | ~3.6k | Automated safety check: Pass | Apache-2.0 | 2 days ago |