Vue d’ensemble
A distributed computing runtime for machine learning training, tuning and model serving. The repository is maintained under ray-project on GitHub. Its primary language is Python. See the [project README](https://github.com/ray-project/ray#readme) for the supported workflows.
Fonctionnalités clés
- A distributed computing runtime for machine learning training, tuning and model serving.
Prérequis, installation et démarrage rapide
Install Ray in a Python environment using the official installation guide. Select additional dependencies for the Ray libraries needed by your workload.
[Read the upstream installation and quickstart instructions](https://github.com/ray-project/ray#readme).
[Read the upstream installation and quickstart instructions](https://github.com/ray-project/ray#readme).
Utilisation
Start with the documented local example, confirm it runs with your resources, then connect it to your application using the supported interface.
[Usage examples and configuration reference](https://github.com/ray-project/ray#readme).
[Usage examples and configuration reference](https://github.com/ray-project/ray#readme).
Compatibilité des modèles et cas d’usage
La compatibilité des modèles n’est pas indiquée dans les métadonnées du dépôt.
Licence et notes sur les risques
GitHub reports Apache-2.0 for this repository. Review the upstream license file; model weights, datasets and dependencies may have separate terms.
Source review 2026-09-05: GitHub search metadata and repository README. No runtime benchmark performed. License metadata: Apache-2.0.
Publication et maintenance
[View upstream releases](https://github.com/ray-project/ray/releases).