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The docs currently state that one can continue the training with a different node count, but actually it only works when re-running the training.
We should add a function that the user can call before restoring the state to re-distribute the saved state to a new parallel config.
The text was updated successfully, but these errors were encountered:
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The docs currently state that one can continue the training with a different node count, but actually it only works when re-running the training.
We should add a function that the user can call before restoring the state to re-distribute the saved state to a new parallel config.
The text was updated successfully, but these errors were encountered: