Skip to main content

Deploy your AI/ML model to Amazon SageMaker for Real-Time Inference and Batch Transform using your own Docker container image.

Project description

inference-server

Deploy your AI/ML model to Amazon SageMaker for Real-Time Inference and Batch Transform using your own Docker container image.

:blue_book: Documentation: https://inference-server.readthedocs.io

Installing

python -m pip install inference-server

Developing

To setup a scratch/development virtual environment (under .venv/), first install Tox. Then run:

tox -e dev

The inference-server package is installed in editable mode inside the .venv/ environment.

Run tests by simply calling tox.

Install code quality Git hooks using pre-commit install --install-hooks.

Terms & Conditions

Copyright 2023 J.P. Morgan Chase & Co.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Contributing

See CONTRIBUTING.md

Project details


Download files

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

Source Distribution

inference_server-1.3.0.tar.gz (31.6 kB view details)

Uploaded Source

Built Distribution

inference_server-1.3.0-py3-none-any.whl (19.3 kB view details)

Uploaded Python 3

File details

Details for the file inference_server-1.3.0.tar.gz.

File metadata

  • Download URL: inference_server-1.3.0.tar.gz
  • Upload date:
  • Size: 31.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for inference_server-1.3.0.tar.gz
Algorithm Hash digest
SHA256 08bc663404dbddb160b7cd8cf9f507b0baed8cd3271d66baf11c1f1f939a58ac
MD5 45ee96fc780d2b455ef2d08c34230627
BLAKE2b-256 7990cf0c8b013ef4794994b5ba8b2ac2b602571b3385ee572cf38186100886ee

See more details on using hashes here.

File details

Details for the file inference_server-1.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for inference_server-1.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 84cbe2682b077a072d3a4774aa9fe9b369a90ce9c5479d3a551a7a92d34743ae
MD5 e68444e7d5084015cbacf555189f81fb
BLAKE2b-256 a382b7f5a11a6a4d26dd814faee9861ea29eab9fc586c779427be9f61a338877

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