Update use_auth_token -> token in example scripts (#25167)
* pytorch examples * tensorflow examples * flax examples --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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@@ -366,14 +366,14 @@ def main():
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model_args.config_name if model_args.config_name else model_args.model_name_or_path,
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cache_dir=model_args.cache_dir,
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revision=model_args.model_revision,
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use_auth_token=True if model_args.use_auth_token else None,
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token=True if model_args.use_auth_token else None,
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)
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tokenizer = AutoTokenizer.from_pretrained(
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model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
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cache_dir=model_args.cache_dir,
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use_fast=model_args.use_fast_tokenizer,
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revision=model_args.model_revision,
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use_auth_token=True if model_args.use_auth_token else None,
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token=True if model_args.use_auth_token else None,
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)
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model = AutoModelForSeq2SeqLM.from_pretrained(
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model_args.model_name_or_path,
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@@ -381,7 +381,7 @@ def main():
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config=config,
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cache_dir=model_args.cache_dir,
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revision=model_args.model_revision,
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use_auth_token=True if model_args.use_auth_token else None,
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token=True if model_args.use_auth_token else None,
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)
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# We resize the embeddings only when necessary to avoid index errors. If you are creating a model from scratch
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