20 Serving LLMs on AMD Instinct alternatives
Serving LLMs on AMD Instinct: 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. 20 agent skills do similar work, most sharing Inference, GPU and Official, ranked by how much they have in common with Serving LLMs on AMD Instinct.
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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.
Also: AMD, Deployment, Inference, Official
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by AMD
AMD's official skill for benchmarking vLLM/SGLang inference and driving GPU kernel optimization with Magpie and TraceLens trace analysis.
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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.
Also: Deployment, GPU, Inference
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by AMD
AMD's official meta-skill: permanently reroutes an agent's image generation, text-to-speech and speech-to-text to a local Lemonade Server instead of a paid cloud API.
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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
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.
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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.
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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 Hugging Face
Deploy and maintain applications on Hugging Face Spaces — SDK choice, GPU hardware, model loading, and debugging.
Also: Deployment, GPU
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by Replicate
Replicate's official skill for running models via its API — predictions, polling, Prefer: wait, webhooks with signature validation, streaming and file handling.
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by AWS Labs
Read-only diagnostics for cluster-wide SageMaker HyperPod failures on EKS or Slurm — CloudFormation errors, EFA health checks, lifecycle scripts, capacity, dangling nodes and autoscaler conflicts.
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by Vercel
Vercel's official deployment skill — inspects project state, picks the right deploy path, and defaults to preview deployments with a claimable URL when no account is linked.
Also: Deployment, Official
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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.
Also: Inference
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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: Inference
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by Hugging Face
Choose and run the right local model with llama.cpp and GGUF — quantisation, hardware fit, and local serving.
Also: Inference
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by Hugging Face
Run machine learning models directly in the browser or Node with Transformers.js — no inference server required.
Also: Inference
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by Anthropic
Authoritative reference for the Claude API and Anthropic SDKs — model IDs, pricing, parameters, streaming, tool use, MCP, agents, prompt caching, and token counting.
Also: Inference
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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.
Also: GPU
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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: GPU
