From f7170067f819222153fcd45682db61279bdfe673 Mon Sep 17 00:00:00 2001 From: Pierre Marcenac Date: Tue, 4 Jun 2024 17:20:55 +0200 Subject: [PATCH] Fix small typo (#6955) --- docs/source/stream.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/stream.mdx b/docs/source/stream.mdx index 8b1ff745041..89c3238429b 100644 --- a/docs/source/stream.mdx +++ b/docs/source/stream.mdx @@ -363,7 +363,7 @@ Lastly, create a simple training loop and start training: ### Save a dataset checkpoint and resume iteration -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. +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. 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: