Snowflake ML release notes

This article contains the release notes for the Snowflake ML, including the following when applicable:

  • Behavior changes

  • New features

  • Customer-facing bug fixes

Note

These notes do not include changes in features that have not been publicly announced. Such features might appear in the Snowflake ML source code but not in the public documentation.

See Snowflake ML: End-to-End Machine Learning for documentation.

Verifying the snowflake-ml-python package

All Snowflake packages are signed, allowing you to verify their origin. To verify the snowflake.ml.python package, follow the steps below:

  1. Install cosign. This example uses the Go installation: Installing cosign with Go.

  2. Download the file from a repository such as PyPi.

  3. Download a .sig file for that release from the GitHub releases page.

  4. Verify the signature using cosign. For example:

cosign verify-blob snowflake_ml_python-1.7.0.tar.gz --key snowflake-ml-python-1.7.0.pub --signature resources.linux.snowflake_ml_python-1.7.0.tar.gz.sig

cosign verify-blob snowflake_ml_python-1.7.0.tar.gz --key snowflake-ml-python-1.7.0.pub --signature resources.linux.snowflake_ml_python-1.7.0
Copy

Note

This example uses the library and signature for version 1.7.0 of the package. Use the filenames of the version you are verifying.

Version 1.7.3 (2025-01-09)

Dependency upgrades

  • fsspec and s3fs must be 2024.6.1 or later and less than 2026.

  • mlflow must be 2.16.0 or later and less than 3.

New features

New Cortex features:

  • Cortex functions now have “snake_case” names. For example, ClassifyText is now classify_text. The old “CamelCase” names still work, but will be removed in a future release.

New Model Registry features:

  • Registry now supports more than 500,000 features.

  • Added user_files argument to Registry.log_model for including images or other files with the model.

  • Added support for handling Hugging Face model configurations with auto-mapping functionality.

New Data features:

  • Added the DataConnector.from_sql constructor.

Bug fixes

Registry bug fixes:

  • Fixed a bug that occurred when providing a non-range index pandas DataFrame as the input to ModelVersion.run.

  • Improved random model registry name generation to avoid collisions.

  • Fixed an issue when inferring a signature or running inference with Snowpark DataFrame that has a column whose type is ARRAY and contains a NULL value.

  • ModelVersion.run now accepts a fully-qualified service name.

  • Fixed an error in log_model for any scikit-learn models with only data preprocessing, including preprocessing-only pipeline models.

Monitoring bug fixes:

  • Fixed an issue with creating monitors using fully-qualified names.

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