Fix missing usage of token (#25382)

* add missing tokens

* fix

---------

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

examples/pytorch/image-pretraining/run_mim_no_trainer.py

@@ -17,6 +17,7 @@ import argparse
 import logging
 import math
 import os
+import warnings
 from pathlib import Path
 
 import datasets
@@ -186,14 +187,20 @@ def parse_args():
         default=None,
         help="Name or path of preprocessor config.",
     )
+    parser.add_argument(
+        "--token",
+        type=str,
+        default=None,
+        help=(
+            "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`)."
+        ),
+    )
     parser.add_argument(
         "--use_auth_token",
         type=bool,
-        default=False,
-        help=(
-            "Will use the token generated when running `huggingface-cli login` (necessary to use this script "
-            "with private models)."
-        ),
+        default=None,
+        help="The `use_auth_token` argument is deprecated and will be removed in v4.34. Please use `token`.",
     )
     parser.add_argument(
         "--trust_remote_code",
@@ -377,6 +384,12 @@ def collate_fn(examples):
 def main():
     args = parse_args()
 
+    if 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 args.token is not None:
+            raise ValueError("`token` and `use_auth_token` are both specified. Please set only the argument `token`.")
+        args.token = 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_mim_no_trainer", args)
@@ -440,7 +453,7 @@ def main():
         args.dataset_config_name,
         data_files=args.data_files,
         cache_dir=args.cache_dir,
-        use_auth_token=True if args.use_auth_token else None,
+        token=args.token,
     )
 
     # If we don't have a validation split, split off a percentage of train as validation.
@@ -457,7 +470,7 @@ def main():
     config_kwargs = {
         "cache_dir": args.cache_dir,
         "revision": args.model_revision,
-        "use_auth_token": True if args.use_auth_token else None,
+        "token": args.token,
         "trust_remote_code": args.trust_remote_code,
     }
     if args.config_name_or_path:
@@ -508,13 +521,14 @@ def main():
             config=config,
             cache_dir=args.cache_dir,
             revision=args.model_revision,
-            token=True if args.use_auth_token else None,
+            token=args.token,
             trust_remote_code=args.trust_remote_code,
         )
     else:
         logger.info("Training new model from scratch")
         model = AutoModelForMaskedImageModeling.from_config(
             config,
+            token=args.token,
             trust_remote_code=args.trust_remote_code,
         )