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Add many missing spaces in adjacent strings (#26751)

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Add missing spaces in adjacent strings
This commit is contained in:
Tom Aarsen
2023-10-12 10:28:40 +02:00
committed by GitHub
parent 3bc65505fc
commit 40ea9ab2a1
154 changed files with 331 additions and 331 deletions
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8
examples/pytorch/summarization/run_summarization.py
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@@ -120,7 +120,7 @@ class ModelArguments:
metadata={
"help": (
"Whether or not to allow for custom models defined on the Hub in their own modeling files. This option"
"should only be set to `True` for repositories you trust and in which you have read the code, as it will"
"should only be set to `True` for repositories you trust and in which you have read the code, as it will "
"execute code present on the Hub on your local machine."
)
},
@@ -205,7 +205,7 @@ class DataTrainingArguments:
metadata={
"help": (
"The maximum total sequence length for validation target text after tokenization. Sequences longer "
"than this will be truncated, sequences shorter will be padded. Will default to `max_target_length`."
"than this will be truncated, sequences shorter will be padded. Will default to `max_target_length`. "
"This argument is also used to override the ``max_length`` param of ``model.generate``, which is used "
"during ``evaluate`` and ``predict``."
)
@@ -271,7 +271,7 @@ class DataTrainingArguments:
default=None,
metadata={
"help": (
"The token to force as the first generated token after the decoder_start_token_id."
"The token to force as the first generated token after the decoder_start_token_id. "
"Useful for multilingual models like mBART where the first generated token"
"needs to be the target language token (Usually it is the target language token)"
)
@@ -556,7 +556,7 @@ def main():
if training_args.label_smoothing_factor > 0 and not hasattr(model, "prepare_decoder_input_ids_from_labels"):
logger.warning(
"label_smoothing is enabled but the `prepare_decoder_input_ids_from_labels` method is not defined for"
"label_smoothing is enabled but the `prepare_decoder_input_ids_from_labels` method is not defined for "
f"`{model.__class__.__name__}`. This will lead to loss being calculated twice and will take up more memory"
)