CARVIEW

MOTORHOMES

Select Language

HTTP/2 301 cache-control: max-age=3600 content-type: text/html; charset=UTF-8 expires: Sat, 27 Dec 2025 10:13:03 GMT location: https://pytorch.org/projects/ray/ server: nginx strict-transport-security: max-age=300 x-pantheon-styx-hostname: styx-fe2-a-68d6cbdd88-lfmdp x-redirect-by: WordPress x-styx-req-id: 3fa83f90-e304-11f0-8a5f-ceb1dfd28036 age: 0 accept-ranges: bytes via: 1.1 varnish, 1.1 varnish, 1.1 varnish, 1.1 varnish date: Sat, 27 Dec 2025 09:13:03 GMT x-served-by: cache-chi-klot8100044-CHI, cache-bom-vanm7210048-BOM, cache-bom-vanm7210081-BOM, cache-bom-vanm7210081-BOM x-cache: MISS, MISS, MISS, MISS x-cache-hits: 0, 0, 0, 0 x-timer: S1766826783.464593,VS0,VE523 vary: Cookie, Cookie content-length: 0 HTTP/2 200 cache-control: public, max-age=60, s-maxage=43200, stale-while-revalidate=86400, stale-if-error=604800 content-encoding: gzip content-type: text/html; charset=UTF-8 link: ; rel="https://api.w.org/" link: ; rel="alternate"; title="JSON"; type="application/json" link: ; rel=shortlink server: nginx strict-transport-security: max-age=300 x-pantheon-styx-hostname: styx-fe2-b-6c64494475-jrcx6 x-styx-req-id: 5f5c67f9-e301-11f0-aab7-525be2786dee x-tec-api-origin: https://pytorch.org x-tec-api-root: https://pytorch.org/wp-json/tribe/events/v1/ x-tec-api-version: v1 age: 1235 accept-ranges: bytes via: 1.1 varnish, 1.1 varnish, 1.1 varnish, 1.1 varnish date: Sat, 27 Dec 2025 09:13:04 GMT x-served-by: cache-chi-klot8100103-CHI, cache-bom-vanm7210032-BOM, cache-bom-vanm7210081-BOM, cache-bom-vanm7210081-BOM x-cache: HIT, MISS, MISS, MISS x-cache-hits: 2, 0, 0, 0 x-timer: S1766826784.000999,VS0,VE249 vary: Accept-Encoding, Cookie, Cookie content-length: 45633 RAY – PyTorch

RAY

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Ray provides a small set of distributed computing primitives that allow developers to scale Python applications across heterogeneous clusters of compute. Ray also includes an ecosystem of higher-level libraries for scaling multimodal data processing, model training, model serving, reinforcement learning, and more.

Ray is used by Python developers and ML / AI practitioners and researchers who are building scalable Python and AI applications. Ray is also adopted by platform and infrastructure engineers who integrate it into their broader infrastructure.

Ray was contributed by Anyscale to the Linux Foundation in September 2025.

Original Source | Taken Source

RAY

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Docs

Tutorials

Resources

Stay in touch for updates, event info, and the latest news