Add token arugment in example scripts (#25172)

* fix

* fix

* fix

* fix

* fix

* fix

* fix

---------

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

examples/flax/text-classification/run_flax_glue.py

@@ -21,6 +21,7 @@ import os
 import random
 import sys
 import time
+import warnings
 from dataclasses import dataclass, field
 from pathlib import Path
 from typing import Any, Callable, Dict, Optional, Tuple
@@ -101,15 +102,21 @@ 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`."
+        },
+    )
 
 
 @dataclass
@@ -321,6 +328,12 @@ 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, framework="flax")
@@ -368,7 +381,7 @@ def main():
         raw_datasets = load_dataset(
             "glue",
             data_args.task_name,
-            use_auth_token=True if model_args.use_auth_token else None,
+            token=model_args.token,
         )
     else:
         # Loading the dataset from local csv or json file.
@@ -381,7 +394,7 @@ def main():
         raw_datasets = load_dataset(
             extension,
             data_files=data_files,
-            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.
@@ -411,17 +424,17 @@ def main():
         model_args.model_name_or_path,
         num_labels=num_labels,
         finetuning_task=data_args.task_name,
-        token=True if model_args.use_auth_token else None,
+        token=model_args.token,
     )
     tokenizer = AutoTokenizer.from_pretrained(
         model_args.model_name_or_path,
         use_fast=not model_args.use_slow_tokenizer,
-        token=True if model_args.use_auth_token else None,
+        token=model_args.token,
     )
     model = FlaxAutoModelForSequenceClassification.from_pretrained(
         model_args.model_name_or_path,
         config=config,
-        token=True if model_args.use_auth_token else None,
+        token=model_args.token,
     )
 
     # Preprocessing the datasets