New Features in May

A100 Support in AWS and GCP

Spell now supports Nvidia's powerful A100 GPU in both Amazon and Google cloud providers. 

Learn more in the docs

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Default to Tensorflow 2 Instead of Tensorflow 1

Runs in Spell will now provide TensorFlow 2 by default. Users who still need TensorFlow 1 can still access it using the --framework tensorflow1 flag. 

Learn more in the docs

jupyter and visual studio code logos

Remote Access to Spell Jupyter Workspaces from VS Code

We now support using Jupyter Workspaces from VS Code. You can easily run your ipynb files on more powerful hardware, quickly see your metrics in the Spell UI, and have all your artifacts saved into the Spell Filesystem whenever you finish with your notebook. 

Learn more in the docs

Specifying Parameters on Runs

In addition to the --param flag on hyper searches, we now support --param on individual runs, allowing you to keep track of specific aspects of a particular training run in a structured manner. This is extra helpful in projects because you can add these parameters as columns in the run table and filter on them to quickly see the effectiveness of specific parameter combinations.

Learn more in the docs

python client update

Python Client Updates

We’ve updated the Spell Python API with new and improved support for resources, hyperparameter searches, models, and model servers. This brings the API to near feature parity with the Spell CLI, and should make Spell a lot easier to call into in scripting contexts going forward! 

Learn more in the docs

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