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/vision/run_image_classification.py

@@ -24,6 +24,7 @@ import logging
 import os
 import sys
 import time
+import warnings
 from dataclasses import asdict, dataclass, field
 from enum import Enum
 from pathlib import Path
@@ -159,15 +160,21 @@ class ModelArguments:
             )
         },
     )
-    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
@@ -257,6 +264,12 @@ 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_image_classification", model_args, data_args, framework="flax")
@@ -338,7 +351,7 @@ def main():
             num_labels=len(train_dataset.classes),
             image_size=data_args.image_size,
             cache_dir=model_args.cache_dir,
-            token=True if model_args.use_auth_token else None,
+            token=model_args.token,
         )
     elif model_args.model_name_or_path:
         config = AutoConfig.from_pretrained(
@@ -346,7 +359,7 @@ def main():
             num_labels=len(train_dataset.classes),
             image_size=data_args.image_size,
             cache_dir=model_args.cache_dir,
-            token=True if model_args.use_auth_token else None,
+            token=model_args.token,
         )
     else:
         config = CONFIG_MAPPING[model_args.model_type]()
@@ -358,7 +371,7 @@ def main():
             config=config,
             seed=training_args.seed,
             dtype=getattr(jnp, model_args.dtype),
-            token=True if model_args.use_auth_token else None,
+            token=model_args.token,
         )
     else:
         model = FlaxAutoModelForImageClassification.from_config(