New job environments based on Python 3.10 are now available for all frameworks.

trainML checkpoints can now be exported to common data locations for use in other environments.

You can now configure automatic checkpointing on a scheduld interval during training for trainML Training Jobs.

trainML jobs can now run shell scripts prior to workload execution and data attachment to further configure the workload environment.

trainML Training and Inference jobs can now be reran on updated data with only two clicks.

With the recent major release of PyTorch 2.0, new trainML job environments are available.

Start building your own ChatGPT-like applications with popular open source Large Language Models like GPT-J, GPT-NeoX, and BloomZ.

CloudBender™ Device Configurations have been expanded to allow attaching public and private Checkpoints to edge inference devices.

Checkpoints and Datasets are now supported output destinations for trainML Training and Inference jobs.

Checkpoints can now be created directly from public or private Hugging Face models.