Add token arugment in example scripts (#25172)

* fix

* fix

* fix

* fix

* fix

* fix

* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

examples/pytorch/text-classification/run_glue.py

@@ -20,6 +20,7 @@ import logging
 import os
 import random
 import sys
+import warnings
 from dataclasses import dataclass, field
 from typing import Optional
 
@@ -188,15 +189,21 @@ class ModelArguments:
         default="main",
         metadata={"help": "The specific model version to use (can be a branch name, tag name or commit id)."},
     )
-    use_auth_token: bool = field(
-        default=False,
+    token: str = field(
+        default=None,
         metadata={
             "help": (
-                "Will use the token generated when running `huggingface-cli login` (necessary to use this script "
-                "with private models)."
+                "The token to use as HTTP bearer authorization for remote files. If not specified, will use the token "
+                "generated when running `huggingface-cli login` (stored in `~/.huggingface`)."
             )
         },
     )
+    use_auth_token: bool = field(
+        default=None,
+        metadata={
+            "help": "The `use_auth_token` argument is deprecated and will be removed in v4.34. Please use `token`."
+        },
+    )
     ignore_mismatched_sizes: bool = field(
         default=False,
         metadata={"help": "Will enable to load a pretrained model whose head dimensions are different."},
@@ -216,6 +223,12 @@ def main():
     else:
         model_args, data_args, training_args = parser.parse_args_into_dataclasses()
 
+    if model_args.use_auth_token is not None:
+        warnings.warn("The `use_auth_token` argument is deprecated and will be removed in v4.34.", FutureWarning)
+        if model_args.token is not None:
+            raise ValueError("`token` and `use_auth_token` are both specified. Please set only the argument `token`.")
+        model_args.token = model_args.use_auth_token
+
     # Sending telemetry. Tracking the example usage helps us better allocate resources to maintain them. The
     # information sent is the one passed as arguments along with your Python/PyTorch versions.
     send_example_telemetry("run_glue", model_args, data_args)
@@ -281,7 +294,7 @@ def main():
             "glue",
             data_args.task_name,
             cache_dir=model_args.cache_dir,
-            use_auth_token=True if model_args.use_auth_token else None,
+            token=model_args.token,
         )
     elif data_args.dataset_name is not None:
         # Downloading and loading a dataset from the hub.
@@ -289,7 +302,7 @@ def main():
             data_args.dataset_name,
             data_args.dataset_config_name,
             cache_dir=model_args.cache_dir,
-            use_auth_token=True if model_args.use_auth_token else None,
+            token=model_args.token,
         )
     else:
         # Loading a dataset from your local files.
@@ -318,7 +331,7 @@ def main():
                 "csv",
                 data_files=data_files,
                 cache_dir=model_args.cache_dir,
-                use_auth_token=True if model_args.use_auth_token else None,
+                token=model_args.token,
             )
         else:
             # Loading a dataset from local json files
@@ -326,7 +339,7 @@ def main():
                 "json",
                 data_files=data_files,
                 cache_dir=model_args.cache_dir,
-                use_auth_token=True if model_args.use_auth_token else None,
+                token=model_args.token,
             )
     # See more about loading any type of standard or custom dataset at
     # https://huggingface.co/docs/datasets/loading_datasets.html.
@@ -361,14 +374,14 @@ def main():
         finetuning_task=data_args.task_name,
         cache_dir=model_args.cache_dir,
         revision=model_args.model_revision,
-        token=True if model_args.use_auth_token else None,
+        token=model_args.token,
     )
     tokenizer = AutoTokenizer.from_pretrained(
         model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
         cache_dir=model_args.cache_dir,
         use_fast=model_args.use_fast_tokenizer,
         revision=model_args.model_revision,
-        token=True if model_args.use_auth_token else None,
+        token=model_args.token,
     )
     model = AutoModelForSequenceClassification.from_pretrained(
         model_args.model_name_or_path,
@@ -376,7 +389,7 @@ def main():
         config=config,
         cache_dir=model_args.cache_dir,
         revision=model_args.model_revision,
-        token=True if model_args.use_auth_token else None,
+        token=model_args.token,
         ignore_mismatched_sizes=model_args.ignore_mismatched_sizes,
     )