Skip to main content

MLflow runtime for MLServer

Project description

MLflow runtime for MLServer

This package provides a MLServer runtime compatible with MLflow models.

Usage

You can install the runtime, alongside mlserver, as:

pip install mlserver mlserver-mlflow

Content Types

The MLflow inference runtime introduces a new dict content type, which decodes an incoming V2 request as a dictionary of tensors. This is useful for certain MLflow-serialised models, which will expect that the model inputs are serialised in this format.

The `dict` content type can be _stacked_ with other content types, like
[`np`](../../docs/user-guide/content-type).
This allows the user to use a different set of content types to decode each of
the dict entries.

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 Distribution

mlserver-mlflow-1.1.0.dev6.tar.gz (8.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mlserver_mlflow-1.1.0.dev6-py3-none-any.whl (9.8 kB view details)

Uploaded Python 3

File details

Details for the file mlserver-mlflow-1.1.0.dev6.tar.gz.

File metadata

  • Download URL: mlserver-mlflow-1.1.0.dev6.tar.gz
  • Upload date:
  • Size: 8.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.9.8

File hashes

Hashes for mlserver-mlflow-1.1.0.dev6.tar.gz
Algorithm Hash digest
SHA256 a1fd84035489eb46cbbdf11434a6e243d6c6b84a46d71e536d47f46685b4a8c2
MD5 4997b1cca1e4a2f668b87d6b3241cd48
BLAKE2b-256 1cca83a7556cfad24f95ead19114b1c4b6deed86fdebae84d50d760ddcbd2432

See more details on using hashes here.

File details

Details for the file mlserver_mlflow-1.1.0.dev6-py3-none-any.whl.

File metadata

File hashes

Hashes for mlserver_mlflow-1.1.0.dev6-py3-none-any.whl
Algorithm Hash digest
SHA256 27d2b6828c36192af654e6e951a5eb4dd173d013528f13a63d48f55c298ef5d9
MD5 85ef625fd28fda5a2fbb5818deae8e73
BLAKE2b-256 9771f98a11e38cb220ac95c5fc418f53fa966acb1345bfff409c8d7da1a908ee

See more details on using hashes here.

Supported by

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