diff --git a/README.md b/README.md
index f42ae74137..7273d87b21 100644
--- a/README.md
+++ b/README.md
@@ -362,11 +362,8 @@ python run_classifier.py \
   --task_name MRPC \
   --do_train \
   --do_eval \
-  --do_lower_case \
   --data_dir $GLUE_DIR/MRPC/ \
-  --vocab_file $BERT_BASE_DIR/vocab.txt \
-  --bert_config_file $BERT_BASE_DIR/bert_config.json \
-  --init_checkpoint $BERT_PYTORCH_DIR/pytorch_model.bin \
+  --bert_model bert-base-uncased \
   --max_seq_length 128 \
   --train_batch_size 32 \
   --learning_rate 2e-5 \
@@ -388,12 +385,9 @@ The data for SQuAD can be downloaded with the following links and should be save
 export SQUAD_DIR=/path/to/SQUAD
 
 python run_squad.py \
-  --vocab_file $BERT_BASE_DIR/vocab.txt \
-  --bert_config_file $BERT_BASE_DIR/bert_config.json \
-  --init_checkpoint $BERT_PYTORCH_DIR/pytorch_model.bin \
+  --bert_model bert-base-uncased \
   --do_train \
   --do_predict \
-  --do_lower_case \
   --train_file $SQUAD_DIR/train-v1.1.json \
   --predict_file $SQUAD_DIR/dev-v1.1.json \
   --train_batch_size 12 \
diff --git a/examples/run_classifier.py b/examples/run_classifier.py
index 0dc5347e2e..938107641e 100644
--- a/examples/run_classifier.py
+++ b/examples/run_classifier.py
@@ -351,11 +351,6 @@ def main():
                         type=str,
                         required=True,
                         help="The name of the task to train.")
-    parser.add_argument("--vocab_file",
-                        default=None,
-                        type=str,
-                        required=True,
-                        help="The vocabulary file that the BERT model was trained on.")
     parser.add_argument("--output_dir",
                         default=None,
                         type=str,
diff --git a/setup.py b/setup.py
index 0cba4e2a5c..d05a955c64 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@ from setuptools import find_packages, setup
 
 setup(
     name="pytorch_pretrained_bert",
-    version="0.1.1",
+    version="0.1.2",
     author="Thomas Wolf, Victor Sanh, Tim Rault, Google AI Language Team Authors",
     author_email="thomas@huggingface.co",
     description="PyTorch version of Google AI BERT model with script to load Google pre-trained models",