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-2024.3.21-py3-none-any.whl (24.3 MB view details)

Uploaded Python 3

File details

Details for the file torchserve_nightly-2024.3.21-py3-none-any.whl.

File metadata

File hashes

Hashes for torchserve_nightly-2024.3.21-py3-none-any.whl
Algorithm Hash digest
SHA256 0fb62951a042df52ea999f28350ee8f90faedcec337407ced8ace421e73b9b91
MD5 f2324e64cb686f9c385a7b0e9b602938
BLAKE2b-256 327676f4a63588055f396e5d9ce306f389021a4766608d23a6ba3f2402cd703d

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