Inferenza, distribuzione e runtime

ray

ray-project/ray

A distributed computing runtime for machine learning training, tuning and model serving.

★ 43,7KStelle
⑂ 8KFork
3565Problemi aperti
PythonLingua
Apache-2.0Licenza
Q85Punteggio editoriale

Panoramica

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.

Funzionalità principali

  • A distributed computing runtime for machine learning training, tuning and model serving.

Requisiti, installazione e avvio rapido

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).

Utilizzo

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).

Compatibilità del modello e casi d'uso

La compatibilità del modello non è indicata nei metadati del repository.

Note su licenza e rischi

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.

Rilascio e manutenzione

[View upstream releases](https://github.com/ray-project/ray/releases).

vllm

vllm-project/vllm

★ 89,5KPython

sglang

sgl-project/sglang

★ 32,2KPython

OpenVINO

openvinotoolkit/openvino

★ 10,6KC++

GPUStack

gpustack/gpustack

★ 5,4KPython