Docs: Fix broken cross-references, i.e. ~transformer. -> ~transformers. (#27740)
~transformer. -> ~transformers.
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@@ -49,7 +49,7 @@ You will then be able to use the auto classes like you would usually do!
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<Tip warning={true}>
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<Tip warning={true}>
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If your `NewModelConfig` is a subclass of [`~transformer.PretrainedConfig`], make sure its
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If your `NewModelConfig` is a subclass of [`~transformers.PretrainedConfig`], make sure its
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`model_type` attribute is set to the same key you use when registering the config (here `"new-model"`).
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`model_type` attribute is set to the same key you use when registering the config (here `"new-model"`).
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Likewise, if your `NewModel` is a subclass of [`PreTrainedModel`], make sure its
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Likewise, if your `NewModel` is a subclass of [`PreTrainedModel`], make sure its
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@@ -43,7 +43,7 @@ AutoModel.register(NewModelConfig, NewModel)
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<Tip warning={true}>
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<Tip warning={true}>
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あなたの`NewModelConfig`が[`~transformer.PretrainedConfig`]のサブクラスである場合、その`model_type`属性がコンフィグを登録するときに使用するキー(ここでは`"new-model"`)と同じに設定されていることを確認してください。
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あなたの`NewModelConfig`が[`~transformers.PretrainedConfig`]のサブクラスである場合、その`model_type`属性がコンフィグを登録するときに使用するキー(ここでは`"new-model"`)と同じに設定されていることを確認してください。
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同様に、あなたの`NewModel`が[`PreTrainedModel`]のサブクラスである場合、その`config_class`属性がモデルを登録する際に使用するクラス(ここでは`NewModelConfig`)と同じに設定されていることを確認してください。
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同様に、あなたの`NewModel`が[`PreTrainedModel`]のサブクラスである場合、その`config_class`属性がモデルを登録する際に使用するクラス(ここでは`NewModelConfig`)と同じに設定されていることを確認してください。
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@@ -151,7 +151,7 @@ class BeamSearchScorer(BeamScorer):
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beam search algorithm).
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beam search algorithm).
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num_beam_hyps_to_keep (`int`, *optional*, defaults to 1):
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num_beam_hyps_to_keep (`int`, *optional*, defaults to 1):
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The number of beam hypotheses that shall be returned upon calling
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The number of beam hypotheses that shall be returned upon calling
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[`~transformer.BeamSearchScorer.finalize`].
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[`~transformers.BeamSearchScorer.finalize`].
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num_beam_groups (`int`, *optional*, defaults to 1):
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num_beam_groups (`int`, *optional*, defaults to 1):
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Number of groups to divide `num_beams` into in order to ensure diversity among different groups of beams.
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Number of groups to divide `num_beams` into in order to ensure diversity among different groups of beams.
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See [this paper](https://arxiv.org/pdf/1610.02424.pdf) for more details.
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See [this paper](https://arxiv.org/pdf/1610.02424.pdf) for more details.
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@@ -444,7 +444,7 @@ class ConstrainedBeamSearchScorer(BeamScorer):
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beam search algorithm).
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beam search algorithm).
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num_beam_hyps_to_keep (`int`, *optional*, defaults to 1):
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num_beam_hyps_to_keep (`int`, *optional*, defaults to 1):
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The number of beam hypotheses that shall be returned upon calling
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The number of beam hypotheses that shall be returned upon calling
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[`~transformer.BeamSearchScorer.finalize`].
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[`~transformers.BeamSearchScorer.finalize`].
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num_beam_groups (`int`, *optional*, defaults to 1):
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num_beam_groups (`int`, *optional*, defaults to 1):
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Number of groups to divide `num_beams` into in order to ensure diversity among different groups of beams.
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Number of groups to divide `num_beams` into in order to ensure diversity among different groups of beams.
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See [this paper](https://arxiv.org/pdf/1610.02424.pdf) for more details.
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See [this paper](https://arxiv.org/pdf/1610.02424.pdf) for more details.
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@@ -650,38 +650,38 @@ class Trainer:
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def add_callback(self, callback):
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def add_callback(self, callback):
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"""
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"""
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Add a callback to the current list of [`~transformer.TrainerCallback`].
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Add a callback to the current list of [`~transformers.TrainerCallback`].
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Args:
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Args:
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callback (`type` or [`~transformer.TrainerCallback`]):
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callback (`type` or [`~transformers.TrainerCallback`]):
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A [`~transformer.TrainerCallback`] class or an instance of a [`~transformer.TrainerCallback`]. In the
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A [`~transformers.TrainerCallback`] class or an instance of a [`~transformers.TrainerCallback`]. In the
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first case, will instantiate a member of that class.
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first case, will instantiate a member of that class.
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"""
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"""
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self.callback_handler.add_callback(callback)
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self.callback_handler.add_callback(callback)
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def pop_callback(self, callback):
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def pop_callback(self, callback):
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"""
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"""
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Remove a callback from the current list of [`~transformer.TrainerCallback`] and returns it.
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Remove a callback from the current list of [`~transformers.TrainerCallback`] and returns it.
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If the callback is not found, returns `None` (and no error is raised).
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If the callback is not found, returns `None` (and no error is raised).
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Args:
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Args:
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callback (`type` or [`~transformer.TrainerCallback`]):
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callback (`type` or [`~transformers.TrainerCallback`]):
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A [`~transformer.TrainerCallback`] class or an instance of a [`~transformer.TrainerCallback`]. In the
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A [`~transformers.TrainerCallback`] class or an instance of a [`~transformers.TrainerCallback`]. In the
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first case, will pop the first member of that class found in the list of callbacks.
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first case, will pop the first member of that class found in the list of callbacks.
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Returns:
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Returns:
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[`~transformer.TrainerCallback`]: The callback removed, if found.
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[`~transformers.TrainerCallback`]: The callback removed, if found.
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"""
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"""
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return self.callback_handler.pop_callback(callback)
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return self.callback_handler.pop_callback(callback)
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def remove_callback(self, callback):
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def remove_callback(self, callback):
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"""
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"""
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Remove a callback from the current list of [`~transformer.TrainerCallback`].
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Remove a callback from the current list of [`~transformers.TrainerCallback`].
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Args:
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Args:
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callback (`type` or [`~transformer.TrainerCallback`]):
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callback (`type` or [`~transformers.TrainerCallback`]):
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A [`~transformer.TrainerCallback`] class or an instance of a [`~transformer.TrainerCallback`]. In the
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A [`~transformers.TrainerCallback`] class or an instance of a [`~transformers.TrainerCallback`]. In the
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first case, will remove the first member of that class found in the list of callbacks.
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first case, will remove the first member of that class found in the list of callbacks.
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"""
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"""
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self.callback_handler.remove_callback(callback)
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self.callback_handler.remove_callback(callback)
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@@ -207,7 +207,7 @@ class TrainerCallback:
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The argument `args`, `state` and `control` are positionals for all events, all the others are grouped in `kwargs`.
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The argument `args`, `state` and `control` are positionals for all events, all the others are grouped in `kwargs`.
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You can unpack the ones you need in the signature of the event using them. As an example, see the code of the
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You can unpack the ones you need in the signature of the event using them. As an example, see the code of the
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simple [`~transformer.PrinterCallback`].
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simple [`~transformers.PrinterCallback`].
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Example:
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Example:
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