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{{ ml-platform-full-name }} release notes

This section shows what changed in {{ ml-platform-full-name }}.

{% note tip %}

To keep up to date with the latest changes and updates, subscribe to our {{ ml-platform-full-name }} Community news channel on Telegram.

{% endnote %}

Release as of 24/01/2025 {#240125}

Added a new configuration, gt4i.1 (1 GPU NVIDIA T4).

Release as of 9/12/24 {#091224}

Discontinued supporting foundation model tuning in {{ ml-platform-name }}. Previously tuned models will no longer be supported along with their base models in accordance with their life cycle.

Use the {{ foundation-models-full-name }} tools to tune models.

Release as of 11/11/24 {#111124}

Now you can use a service agent to work with {{ yandex-cloud }} services from {{ ml-platform-name }} notebooks, e.g., issue authorization tokens. To enable this feature in a community, follow this guide. For more information on how service agents work, see the {{ iam-name }} documentation.

Release as of 02/09/24 {#020924}

Release as of 30/07/24 {#300724}

  • Added a feature to create communities in different availability zones: {{ region-id }}-a and {{ region-id }}-b.
  • You can now connect to your nodes an additional disk of 10 to 4,096 GB.
  • Fixed some bugs and added minor performance improvements.

Release as of 04/07/24 {#040724}

Release as of 18/06/24 {#180624}

  • Now you can deploy node instances in different availability zones: {{ region-id }}-a and {{ region-id }}-b.
  • Now you can rerun jobs.
  • Python 3.7 is no longer supported.
  • Fixed some bugs and added minor performance improvements.

Release as of 03/04/24 {#030424}

  1. Updated configurations of {{ dataproc-name }} temporary clusters.
  2. Now you can use XGBoost and LightGBM models to deploy nodes from models.
  3. Added delivering input variables in fulfillment APIs.
  4. Improved creating nodes from Docker images.
  5. Fixed some bugs and added minor performance improvements.

Release as of 27/03/24 {#270324}

Model tuning in {{ ml-platform-name }} now works based on the new {{ gpt-pro }} model.

Release as of 01/03/24 {#010324}

The Serverless mode is no longer supported.

Release as of 27/02/24 {#270224}

  1. Added the option to run a notebook in Dedicated mode to the API.
  2. Improved logs and metrics for nodes.
  3. Fixed bugs and added minor improvements in platform performance.

Release as of 29/01/24 {#290124}

  1. Updated the NVIDIA driver to version 535.
  2. Added support for multi-login to multiple organizations in various federations.
  3. Added the option to pause and resume a running node.
  4. Fixed bugs and added minor improvements in platform performance.

Release as of 15/01/24 {#150124}

  1. Added self-service problem-solving tools to the project page.
  2. In {{ ml-platform-name }} Jobs, now you can use your project resources: secrets, S3 connectors, environment dockers, datasets, and project disk.
  3. Fixed bugs and added minor improvements in platform performance.

Release as of 20/12/23 {#201223}

  1. Added new configuration, gt4.1 (1 GPU NVIDIA T4).
  2. The g2.mig configuration (1 GPU MIG NVIDIA Ampere A100) is obsolete.
  3. A new node type from the model resource is available.
  4. Selecting a configuration in {{ dd }} mode will display its current availability.
  5. Fixed bugs and added minor improvements in platform performance.

Release as of 10/10/23 {#101023}

  1. You can test fine-tuned {{ yagpt-name }} models right in {{ ml-platform-name }}. {{ yagpt-name }} Playground in {{ ml-platform-name }} is available after fine-tuning to users with access to {{ yagpt-full-name }}.
  2. You can now connect your {{ ml-platform-name }} project to {{ jlab }}Lab from a local IDE.
  3. Fixed bugs and added minor improvements in platform performance.

Release as of 25/09/23 {#250923}

  1. With {{ ml-platform-name }} Jobs, cloud computing resources in {{ ml-platform-name }} can now be used from a user's local environment.
  2. {{ ml-platform-name }} projects now have a new type of resources: Models.
  3. Optimized JupyterLab 3 (available in dedicated mode) by adding new extensions.
  4. {{ yagpt-name }} model tuning is now available at the Preview stage.
  5. Fixed bugs and added minor improvements in platform performance.

Release as of 18/09/23 {#180923}

  1. A new DS Default (Python 3.10) system image is used by default.
  2. Community administrators can now manage permissions to use the functionality.
  3. Improved working with community and project lists.
  4. Fixed bugs and added minor improvements in platform performance.

Release as of 21/07/23 {#210723}

  1. Updated the {{ jlab }}Lab extension for working with GIT.
  2. Community administrators can now manage permissions to use computing resources.
  3. Community and project members can now be added before they accept an invitation to join an organization.
  4. Improved the Docker image build editor.
  5. Added an example of operations with {{ yagpt-full-name }} to initial notebooks.
  6. The process of starting a project is now more obvious and transparent.
  7. Fixed bugs and added minor improvements in platform performance.

Release as of 20/06/23 {#200623}

  1. Added a page with a [list of all user projects]({{ link-datasphere-main }}projects).
  2. Updated initial notebooks.
  3. Fixed bugs and added minor improvements in platform performance.

Release as of 23/05/23 {#230523}

  1. {{ ml-platform-name }} now supports a new {{ dd }} operation mode.
  2. In the {{ dd }} mode, the IDE version is updated to JupyterLab 3.5.3.
  3. You can now select an organization in an optimized way.
  4. Operations with community and project members are now easier to perform.
  5. Fixed bugs and added minor improvements in platform performance.

Release as of 29/03/23 {#290323}

  1. You can now work with labels to label resources.
  2. Fixed bugs and added minor improvements.

Release as of 24/03/23 {#240323}

  1. Added a tool to migrate projects to the new {{ ml-platform-name }} version.
  2. Fixed bugs and added minor improvements.

Release as of 02/03/23 {#020323}

  1. You can now use the new {{ ml-platform-name }} version via the API.
  2. Fixed bugs and added minor improvements.

Release as of 19/01/23 {#190123}

  1. The service now displays inherited roles of community and project members.
  2. Optimized the advanced settings for projects.
  3. Updated the snippets for working with S3, Yandex Disk, and Google Drive.
  4. Fixed bugs and added minor improvements.

Release as of 20/10/22 {#201022}

Greatly improved the Apache Spark™ cluster functionality:

  1. {{ ml-platform-name }} now has a new type of resources: {{ dataproc-name }} templates.
  2. You can now configure a livy session when using {{ dataproc-name }} clusters.
  3. {{ ml-platform-name }} now supports the Spark SQL library.

Release as of 23/09/22 {#230922}

Meet our large {{ ml-platform-name }} update: new interface, communities, resources, and many other features for ML development.

{% include old-releases %}