Jobs Overview

Jobs Overview · Hugging Face Hub documentation Jobs Overview Hub 🏡 View all docsAWS Trainium & InferentiaAccelerateArgillaAutoTrainBitsandbytesCLIChat UIDataset viewerDatasetsDeploying on AWSDiffusersDistilabelEvaluateGoogle CloudGoogle TPUsGradioHubHub Python LibraryHuggingface.jsInference Endpoints (dedicated)Inference ProvidersKernelsLeRobotLeaderboardsLightevalMicrosoft AzureOpenEnvOptimumPEFTReachy MiniSafetensorsSentence TransformersTRLTasksText Embeddings InferenceText Generation InferenceTokenizersTrackioTransformersTransformers.jsXetsmolagentstimm Search documentation EN Join the Hugging Face community and get access to the augmented documentation experience Collaborate on models, datasets and Spaces Faster examples with accelerated inference Switch between documentation themes to get started Copy page Jobs Overview Run compute jobs on Hugging Face infrastructure with a familiar UV & Docker-like interface! UV & Docker-like CLI uv,run,ps,logs,stats,inspect Any Hardware CPUs to A100s & TPUs Run Anything UV, Docker, HF Spaces & more Pay-as-you-go Pay only for seconds used The Hugging Face Hub provides compute for AI and data workflows via Jobs. Jobs runs on Hugging Face infrastructure and aim at providing AI builders, Data engineers, developers and AI agents an easy access to cloud infrastructure to run their workloads. They are ideal to fine tune AI models and run inference with GPUs, but also for data ingestion and processing as well. A job is defined with a command to run (e.g. a UV or python command), a hardware flavor (CPU, GPU, TPU), and optionally a Docker image from Hugging Face Spaces or Docker Hub. Many jobs can run in parallel, which is useful e.g. for parameter tuning or parallel inference and data processing. Run Jobs from anywhere There are multiple tools you can use to run jobs: - the`hf` Command Line Interface (see the CLI installation steps and the Jobs CLI documentation for more information)