Add many missing spaces in adjacent strings (#26751)
Add missing spaces in adjacent strings
This commit is contained in:
@@ -82,7 +82,7 @@ class DataTrainingArguments:
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default=None,
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metadata={
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"help": (
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"The name of the text column in the input dataset or a CSV/JSON file."
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"The name of the text column in the input dataset or a CSV/JSON file. "
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'If not specified, will use the "sentence" column for single/multi-label classifcation task.'
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)
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},
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@@ -120,7 +120,7 @@ class DataTrainingArguments:
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default=None,
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metadata={
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"help": (
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"The name of the label column in the input dataset or a CSV/JSON file."
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"The name of the label column in the input dataset or a CSV/JSON file. "
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'If not specified, will use the "label" column for single/multi-label classifcation task'
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)
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},
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@@ -248,7 +248,7 @@ class ModelArguments:
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metadata={
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"help": (
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"Whether or not to allow for custom models defined on the Hub in their own modeling files. This option"
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"should only be set to `True` for repositories you trust and in which you have read the code, as it will"
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"should only be set to `True` for repositories you trust and in which you have read the code, as it will "
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"execute code present on the Hub on your local machine."
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)
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},
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@@ -552,7 +552,7 @@ def main():
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if data_args.max_seq_length > tokenizer.model_max_length:
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logger.warning(
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f"The max_seq_length passed ({data_args.max_seq_length}) is larger than the maximum length for the"
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f"The max_seq_length passed ({data_args.max_seq_length}) is larger than the maximum length for the "
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f"model ({tokenizer.model_max_length}). Using max_seq_length={tokenizer.model_max_length}."
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)
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max_seq_length = min(data_args.max_seq_length, tokenizer.model_max_length)
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@@ -209,7 +209,7 @@ class ModelArguments:
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metadata={
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"help": (
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"Whether or not to allow for custom models defined on the Hub in their own modeling files. This option"
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"should only be set to `True` for repositories you trust and in which you have read the code, as it will"
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"should only be set to `True` for repositories you trust and in which you have read the code, as it will "
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"execute code present on the Hub on your local machine."
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)
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},
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@@ -456,7 +456,7 @@ def main():
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if data_args.max_seq_length > tokenizer.model_max_length:
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logger.warning(
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f"The max_seq_length passed ({data_args.max_seq_length}) is larger than the maximum length for the"
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f"The max_seq_length passed ({data_args.max_seq_length}) is larger than the maximum length for the "
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f"model ({tokenizer.model_max_length}). Using max_seq_length={tokenizer.model_max_length}."
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)
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max_seq_length = min(data_args.max_seq_length, tokenizer.model_max_length)
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@@ -162,7 +162,7 @@ def parse_args():
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default=False,
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help=(
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"Whether or not to allow for custom models defined on the Hub in their own modeling files. This option"
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"should only be set to `True` for repositories you trust and in which you have read the code, as it will"
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"should only be set to `True` for repositories you trust and in which you have read the code, as it will "
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"execute code present on the Hub on your local machine."
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),
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)
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@@ -189,7 +189,7 @@ def parse_args():
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default="all",
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help=(
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'The integration to report the results and logs to. Supported platforms are `"tensorboard"`,'
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' `"wandb"`, `"comet_ml"` and `"clearml"`. Use `"all"` (default) to report to all integrations.'
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' `"wandb"`, `"comet_ml"` and `"clearml"`. Use `"all"` (default) to report to all integrations. '
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"Only applicable when `--with_tracking` is passed."
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),
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)
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@@ -173,7 +173,7 @@ class ModelArguments:
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metadata={
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"help": (
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"Whether or not to allow for custom models defined on the Hub in their own modeling files. This option"
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"should only be set to `True` for repositories you trust and in which you have read the code, as it will"
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"should only be set to `True` for repositories you trust and in which you have read the code, as it will "
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"execute code present on the Hub on your local machine."
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)
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},
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