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-2024.3.26-py3-none-any.whl (24.3 MB view details)

Uploaded Python 3

File details

Details for the file torchserve_nightly-2024.3.26-py3-none-any.whl.

File metadata

File hashes

Hashes for torchserve_nightly-2024.3.26-py3-none-any.whl
Algorithm Hash digest
SHA256 57f19e659f46ac9d72150449da05906c6a5e3a029704f4dce73a114cb38ffd35
MD5 0d8c574be95dcd825548729e39644880
BLAKE2b-256 86d53bea9f304995b06d12d3d33143eff391f76e431b4209411e04ea85e8bcb4

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