20 NVIDIA TAO RT-DETR alternatives
NVIDIA TAO RT-DETR: Trains, distils, quantises, evaluates, exports and runs inference for RT-DETR real-time object detection in NVIDIA TAO, routing training through AutoML hyperparameter search by default. 20 agent skills do similar work, most sharing NVIDIA, GPU and Inference, ranked by how much they have in common with NVIDIA TAO RT-DETR.
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by NVIDIA
Inspects the host's hardware, OS, CUDA driver and existing tooling, recommends one Holoscan SDK install method with a reason, then hands off to the matching install skill.
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by NVIDIA
Runs NVIDIA's NV-Reason-CXR-3B chest X-ray reasoning model through a documented wrapper, locally on GPU or via the public Hugging Face Space, and returns the model's full reasoning trace as engineering evidence.
Also: Computer Vision, GPU, Inference, NVIDIA
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by Hugging Face
Fine-tune object detection, image classification and SAM/SAM2 segmentation models on Hugging Face Jobs cloud GPUs, with dataset validation before you spend GPU minutes.
Also: Computer Vision, Fine-tuning, GPU
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by NVIDIA
NVIDIA's official skill for generating and validating runnable gst-launch DeepStream pipelines from a plain-language description of the video inference you want.
Also: Computer Vision, Inference, NVIDIA
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by NVIDIA
Turns a plain-language weather question into a working Earth2Studio inference script — picks the AI forecast model, a compatible data source, an IO backend, and the step count.
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by NVIDIA
NVIDIA's official skill for deploying and operating Nemotron Speech (Riva) NIMs — ASR, text-to-speech and translation, cloud-hosted or self-hosted on your own GPUs.
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by NVIDIA
Picks the right vLLM or SGLang runtime for your Jetson generation and JetPack version, then produces a working OpenAI-compatible serving command.
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by AMD
AMD's official skill for CPU inference: brings up a single vLLM + zentorch endpoint on an EPYC server, sized to the socket it runs on.
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by NVIDIA
Deploy, configure and troubleshoot the NVIDIA RAG Blueprint from your agent — Docker Compose, Helm or library, with feature toggles for VLM, guardrails and agentic RAG.
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by Hugging Face
Fine-tune language and vision models with TRL or Unsloth — supervised, preference, and reinforcement training methods.
Also: Fine-tuning, GPU
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by NVIDIA
NVIDIA's official skill for asking a vision-language model fresh questions about recorded video through the Video Search and Summarization blueprint — only when the pixels actually need looking at.
Also: Computer Vision, NVIDIA
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by NVIDIA
NVIDIA's official skill for building synthetic datasets with NeMo Data Designer — describe the data you want and the agent writes a declarative generation pipeline, column by column.
Also: Fine-tuning, NVIDIA
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by AMD
AMD's official skill for standing up a vLLM endpoint on Instinct MI300X/MI325X/MI350X/MI355X GPUs — detection, recipe lookup, launch and health check in one flow.
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by NVIDIA
NVIDIA's official skill for bringing up Dynamo inference routing — pick a router mode, enable KV-aware routing, and smoke-test the frontend endpoint before claiming anything works.
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by NVIDIA
Diagnoses wrong gradients in differentiable NVIDIA Warp programs by measuring first — comparing autodiff against finite differences on a shrunk reproduction before proposing any fix.
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by NVIDIA
GPU-accelerated Mean-CVaR and Mean-Variance portfolio construction with NVIDIA cuOpt: scenario generation, variance-capped SOCP allocations, efficient frontiers, backtests and rebalancing.
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by NVIDIA
NVIDIA's official skill for DALI's imperative dynamic-mode API — write GPU data loading as ordinary Python, or migrate an existing pipeline-mode graph across.
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by NVIDIA
NVIDIA's official onboarding skill for CUDA-Q — installs the platform, writes your first quantum kernel, picks a GPU simulator and routes you to real QPU hardware.
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by NVIDIA
NVIDIA's own guidance for moving pandas workloads onto GPU DataFrames with cuDF and dask-cuDF — when it pays off, and how to keep results identical.
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by Hugging Face
Train bi-encoders, rerankers, SPLADE sparse encoders and ColBERT multi-vector models with the loss, evaluator and template each type actually needs.
Also: Fine-tuning
