“Model inference”

Connects NemoClaw to a local inference server.

Connects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama…

Work with Prime Intellect products via the prime CLI and Python SDKs - verifiers environments and the Environments Hub, evaluations (local and hosted), Hosted…

Use verified service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.

Start and test the prime-rl inference server.

Run 150+ AI apps via inference.sh CLI (infsh) — image generation, video creation, LLMs, search, 3D, social automation.

The core OpenAI-compatible inference endpoints: chat completions, embeddings, images, audio (TTS/STT), moderations, rerank, and the Responses API.

Run 150+ AI apps (image, video, LLM) via inference.sh CLI.

llama.cpp local GGUF inference + HF Hub model discovery.

llama.cpp local GGUF inference + HF Hub model discovery.

llama.cpp local GGUF inference + HF Hub model discovery.

Running AI models locally with Ollama and llama.cpp.

Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub.

Use when predicting molecular structures (proteins, nucleic acids, small molecules, and complexes) with the Chai-1 foundation model via local inference or the…

Pick the right serving container for a SageMaker model deployment and find its current image URI.

Pull pre-computed ortholog calls from public databases (OrthoDB, Ensembl Compara, OMA browser, eggNOG, PANTHER, KEGG Orthology, HomoloGene) via their REST APIs.

Implement "Sign In with OpenRouter" using OAuth PKCE — framework-agnostic, no SDK or client registration required.

Use this skill when building, deploying, evaluating, debugging, or measuring latency for the DeepStream SOP Inference Microservice — a GPU-accelerated FastAPI…

Choose OpenRouter models and routers, query live catalog data, use structured outputs and batch inference, and debug routing with metadata.

Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces…

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching.

Test availability, benchmark speed, and add a new model to any OpenAI-compatible provider in models.json.

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency.

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching.