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Fix small typo (#6955)
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docs/source/stream.mdx

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@@ -363,7 +363,7 @@ Lastly, create a simple training loop and start training:
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### Save a dataset checkpoint and resume iteration
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If you training loop stops, you may want to restart the training from where it was. To do so you can save a checkpoint of your model and optimizers, as well as your data loader.
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If your training loop stops, you may want to restart the training from where it was. To do so you can save a checkpoint of your model and optimizers, as well as your data loader.
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Iterable datasets don't provide random access to a specific example index to resume from, but you can use [`IterableDataset.state_dict`] and [`IterableDataset.load_state_dict`] to resume from a checkpoint instead, similarly to what you can do for models and optimizers:
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