Add use_auth to load_datasets for private datasets to PT and TF examples (#16521)

* fix formatting and remove use_auth

* Add use_auth_token to Flax examples

examples/flax/text-classification/run_flax_glue.py

@@ -337,7 +337,11 @@ def main():
     # download the dataset.
     if data_args.task_name is not None:
         # Downloading and loading a dataset from the hub.
-        raw_datasets = load_dataset("glue", data_args.task_name)
+        raw_datasets = load_dataset(
+            "glue",
+            data_args.task_name,
+            use_auth_token=True if model_args.use_auth_token else None,
+        )
     else:
         # Loading the dataset from local csv or json file.
         data_files = {}
@@ -346,7 +350,11 @@ def main():
         if data_args.validation_file is not None:
             data_files["validation"] = data_args.validation_file
         extension = (data_args.train_file if data_args.train_file is not None else data_args.valid_file).split(".")[-1]
-        raw_datasets = load_dataset(extension, data_files=data_files)
+        raw_datasets = load_dataset(
+            extension,
+            data_files=data_files,
+            use_auth_token=True if model_args.use_auth_token else None,
+        )
     # See more about loading any type of standard or custom dataset at
     # https://huggingface.co/docs/datasets/loading_datasets.html.
 
@@ -372,12 +380,21 @@ def main():
 
     # Load pretrained model and tokenizer
     config = AutoConfig.from_pretrained(
-        model_args.model_name_or_path, num_labels=num_labels, finetuning_task=data_args.task_name
+        model_args.model_name_or_path,
+        num_labels=num_labels,
+        finetuning_task=data_args.task_name,
+        use_auth_token=True if model_args.use_auth_token else None,
     )
     tokenizer = AutoTokenizer.from_pretrained(
-        model_args.model_name_or_path, use_fast=not model_args.use_slow_tokenizer
+        model_args.model_name_or_path,
+        use_fast=not model_args.use_slow_tokenizer,
+        use_auth_token=True if model_args.use_auth_token else None,
+    )
+    model = FlaxAutoModelForSequenceClassification.from_pretrained(
+        model_args.model_name_or_path,
+        config=config,
+        use_auth_token=True if model_args.use_auth_token else None,
     )
-    model = FlaxAutoModelForSequenceClassification.from_pretrained(model_args.model_name_or_path, config=config)
 
     # Preprocessing the datasets
     if data_args.task_name is not None: