diff --git a/README.md b/README.md
index c938569..3c590fe 100644
--- a/README.md
+++ b/README.md
@@ -26,7 +26,6 @@ pip install transformers==3.3.1
 # pip install happytransformer -U
 pip install --editable happy-transformer
 pip install tensorboardX
-mkdir pred_results
 
 # Optional:
 # Install apex following https://github.com/NVIDIA/apex#linux
@@ -39,13 +38,16 @@ pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cud
 
 For masked language models:
 ```bash
+# folder for your personal results
+mkdir pred_results
+
 python src/mlm_predict.py bert-base \
         data/test.core.masked.txt \
-        results/bert-base.test.core.output.jsonl
+        pred_results/bert-base.test.core.output.jsonl
 
 python src/mlm_predict.py bert-base \
         data/test.all.masked.txt \
-        results/bert-base.test.all.output.jsonl
+        pred_results/bert-base.test.all.output.jsonl
 ```
 
 Note that `bert-base` can be replaced by any model name in `[bert-base, bert-large, roberta-base, roberta-large]`.
@@ -54,7 +56,7 @@ For left-to-right language models:
 ```bash
 python src/gpt_predict.py gpt \
         data/test.core.masked.txt \
-        results/gpt.test.core.output.jsonl 
+        pred_results/gpt.test.core.output.jsonl 
 ```
 
 ### Fine-tune a MLM model 
@@ -77,10 +79,10 @@ CUDA_VISIBLE_DEVICES=0 python src/finetune_mlm.py \
 ```
 
 ```bash 
-python src/mlm_infer.py \
+python src/mlm_predict.py \
         reload_bert:saved_models/finetuned_bert_large \
         data/test.core.masked.txt \
-        results/test.core.output.jsonl
+        pred_results/bert-large-finetuned.test.core.output.jsonl
 ```
 
 ## Evaluation on Validation Set
diff --git a/happy-transformer/happytransformer/happy_transformer.py b/happy-transformer/happytransformer/happy_transformer.py
index 74b6283..adc85c2 100644
--- a/happy-transformer/happytransformer/happy_transformer.py
+++ b/happy-transformer/happytransformer/happy_transformer.py
@@ -90,7 +90,7 @@ def predict_mask(self, text: str, options=None, num_results=1):
         if self.mlm is None:
             self._get_masked_language_model()
             
-        if self.gpu_support:
+        if self.gpu_support == "cuda":
             self.mlm.to("cuda")
 
         if self.model_name in self.tag_one_transformers:
@@ -251,7 +251,7 @@ def _get_prediction_softmax(self, text):
         # Convert inputs to PyTorch tensors
         tokens_tensor = torch.tensor([indexed_tokens])
 
-        if self.gpu_support:
+        if self.gpu_support == "cuda":
             tokens_tensor = tokens_tensor.to('cuda')
 
         with torch.no_grad():
@@ -259,7 +259,7 @@ def _get_prediction_softmax(self, text):
             if self.model_name != "ROBERTA":
                 segments_ids = self._get_segment_ids(text)
                 segments_tensors = torch.tensor([segments_ids])
-                if self.gpu_support:
+                if self.gpu_support == "cuda":
                     segments_tensors = segments_tensors.to('cuda')
                 outputs = self.mlm(tokens_tensor, token_type_ids=segments_tensors)
             else:
diff --git a/src/gpt_predict.py b/src/gpt_predict.py
index 32fb889..472f125 100644
--- a/src/gpt_predict.py
+++ b/src/gpt_predict.py
@@ -15,7 +15,7 @@
     model_str = sys.argv[1]
     input_filename = sys.argv[2]
     output_filename = sys.argv[3]
-    cuda = True
+    cuda = torch.cuda.is_available() # TRUE if NVIDIA GPU is available
     model = None
     if model_str.startswith("reload_"):
         if model_str.startswith("reload_bert"):