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Finish removing references to InstructDataset
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docs/source/deep_dives/configs.rst

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@@ -119,7 +119,7 @@ keyword arguments not specified in the config if we'd like:
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tokenizer: ModelTokenizer,
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train_on_input: bool = True,
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max_seq_len: int = 512,
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) -> InstructDataset:
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) -> SFTDataset:
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from torchtune import config
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docs/source/tutorials/datasets.rst

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@@ -495,10 +495,6 @@ that :class:`~torchtune.datasets.SFTDataset` and :class:`~torchtune.datasets.Tex
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you to create your own dataset class for more flexibility. Let's walk through the :class:`~torchtune.datasets.PreferenceDataset`,
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which has custom functionality for RLHF preference data, as an example to understand what you'll need to do.
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If you take a look at the code for the :class:`~torchtune.datasets.PreferenceDataset` class,
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you'll notice it's quite similar to :class:`~torchtune.datasets.InstructDataset` with a few
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adjustments for chosen and rejected samples in preference data.
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.. code-block:: python
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chosen_message = [

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