Skip to main content

TorchServe is a tool for serving neural net models for inference

Project description

TorchServe is a flexible and easy to use tool for serving PyTorch models in production.

Use the TorchServe CLI, or the pre-configured Docker images, to start a service that sets up HTTP endpoints to handle model inference requests.

Installation

Full installation instructions are in the project repo: https://github.com/pytorch/serve/blob/master/README.md

Source code

You can check the latest source code as follows:

git clone https://github.com/pytorch/serve.git

Citation

If you use torchserve in a publication or project, please cite torchserve: https://github.com/pytorch/serve

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

torchserve_nightly-2024.10.17-py3-none-any.whl (42.2 MB view details)

Uploaded Python 3

File details

Details for the file torchserve_nightly-2024.10.17-py3-none-any.whl.

File metadata

File hashes

Hashes for torchserve_nightly-2024.10.17-py3-none-any.whl
Algorithm Hash digest
SHA256 ffb3cc8520d266dd93f7f9a4fe3541604e1411233c50286c63baaa63d148fbc1
MD5 68706aae557325ff0429bbb63bcd5537
BLAKE2b-256 a55d47fb33bec41d262480908206d0ce9f5b9c558b49b77400bae73411380eb6

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page