Run and manage Jobs

Run and manage Jobs · Hugging Face Hub Python Library documentation Run and manage Jobs Hub Python Library 🏡 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 Ctrl+K mainv1.26.0v1.25.1v1.24.0v1.23.0.rc0v1.22.0v1.21.0.rc0v1.20.1v1.19.0v1.16.2v1.12.1v1.11.0v1.10.1v1.9.1v1.7.1v1.6.0v1.5.0v1.4.0v1.3.7v1.2.4v1.1.7v1.0.0.rc7v0.36.2v0.35.3v0.34.6v0.33.5v0.32.6v0.31.4v0.30.2v0.29.3v0.28.1v0.27.1v0.26.5v0.25.2v0.24.7v0.23.5v0.22.2v0.21.4v0.20.3v0.19.3v0.18.0.rc0v0.17.3v0.16.3v0.15.1v0.14.1v0.13.4v0.12.1v0.11.0v0.10.1v0.9.1v0.8.1v0.7.0.rc0v0.6.0.rc0v0.5.1 CNDEENFRHIKOORTA 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 Run and manage Jobs The Hugging Face Hub provides compute for AI and data workflows via Jobs. For a general overview of Jobs and pricing, see the Hub Jobs documentation. A job runs on Hugging Face infrastructure and are defined with a command to run (e.g. a python command), a Docker Image from Hugging Face Spaces or Docker Hub, and a hardware flavor (CPU, GPU, TPU). This guide will show you how to interact with Jobs on the Hub, especially: - Run a job. - Check job status. - Select the hardware. - Configure environment variables and secrets. - Run UV scripts. If you want to run and manage a job on the Hub, your machine must be logged in. If you are not, please refer to this section. In the rest o