diff --git a/README.md b/README.md
index 4d9a413786d67d7d24e6b2cee88baf8d8719706f..1e6c5d31a8d925fd8475e29a6aabf333af48dd1e 100755
--- a/README.md
+++ b/README.md
@@ -36,10 +36,9 @@ We provide scripts for reproducing all the results from our paper. You can train
 
 **Recent updates**
 
-* July 22, 2018
-  * Thanks for recent commits that contains RDN and RCAN. Please see ``code/demo.sh`` to train/test those models.
-  * Now the dataloader is much stable than the previous version. Please erase ``DIV2K/bin`` folder that is created before this commit. Also, please avoid to use ``--ext bin`` argument. Our code will automatically pre-decode png images before training. If you do not have enough spaces(~10GB) in your disk, we recommend ``--ext img``(But SLOW!).
-
+* Oct 18, 2018
+  * with ``--pre_train download``, pretrained models will be automatically downloaded from server.
+  * Supports video input/output (inference only). Try with ``--data_test video --dir_demo [video file directory]``.
 
 ## Code
 Clone this repository into any place you want.
@@ -167,3 +166,8 @@ sh demo.sh
   * Compatible with PyTorch 0.4.0
   * Please use the legacy/0.3.1 branch if you are using the old version of PyTorch.
   * Minor bug fixes
+
+* July 22, 2018
+  * Thanks for recent commits that contains RDN and RCAN. Please see ``code/demo.sh`` to train/test those models.
+  * Now the dataloader is much stable than the previous version. Please erase ``DIV2K/bin`` folder that is created before this commit. Also, please avoid to use ``--ext bin`` argument. Our code will automatically pre-decode png images before training. If you do not have enough spaces(~10GB) in your disk, we recommend ``--ext img``(But SLOW!).
+
diff --git a/experiment/model/.gitignore b/experiment/model/.gitignore
deleted file mode 100644
index fc5177b5dc4c273b2ac4e2677911334f3509426e..0000000000000000000000000000000000000000
--- a/experiment/model/.gitignore
+++ /dev/null
@@ -1,3 +0,0 @@
-*
-!.gitignore
-!*.pt
diff --git a/experiment/model/MDSR_baseline.pt b/experiment/model/MDSR_baseline.pt
deleted file mode 100644
index 307c374aa623a545769faeb5a2fa3092b4f268f5..0000000000000000000000000000000000000000
Binary files a/experiment/model/MDSR_baseline.pt and /dev/null differ
diff --git a/experiment/model/MDSR_baseline_jpeg.pt b/experiment/model/MDSR_baseline_jpeg.pt
deleted file mode 100644
index 94e6a6ac12d52b191df6f6e9354917edf6e7c984..0000000000000000000000000000000000000000
Binary files a/experiment/model/MDSR_baseline_jpeg.pt and /dev/null differ
diff --git a/src/data/__init__.py b/src/data/__init__.py
index 26b43f2992d89b3605b2c2663159febeebc35555..827320054c221b7f7e4b25baec2e2a57259807f0 100644
--- a/src/data/__init__.py
+++ b/src/data/__init__.py
@@ -6,6 +6,7 @@ from torch.utils.data import ConcatDataset
 class MyConcatDataset(ConcatDataset):
     def __init__(self, datasets):
         super(MyConcatDataset, self).__init__(datasets)
+        self.train = datasets[0].train
 
     def set_scale(self, idx_scale):
         for d in self.datasets:
diff --git a/src/model/__init__.py b/src/model/__init__.py
index a2cc30d63fd417b965be92135e97cdfe7ee6cda8..ee35f5c932f28ff3bd1a4822ffc3054d5340965d 100644
--- a/src/model/__init__.py
+++ b/src/model/__init__.py
@@ -75,7 +75,7 @@ class Model(nn.Module):
 
         for s in save_dirs: torch.save(target.state_dict(), s)
 
-    def load(self, apath, pre_train='.', resume=-1, cpu=False):
+    def load(self, apath, pre_train='', resume=-1, cpu=False):
         if cpu:
             kwargs = {'map_location': lambda storage, loc: storage}
         else:
@@ -97,7 +97,7 @@ class Model(nn.Module):
                     model_dir=dir_model,
                     **kwargs
                 )
-            elif pre_train != '':
+            elif pre_train:
                 print('Load the model from {}'.format(pre_train))
                 load_from = torch.load(pre_train, **kwargs)
         else:
diff --git a/src/trainer.py b/src/trainer.py
index a05fa0a515b2c309e0a13a9606db54c5e9fd7527..fb73373d2702e7940ad997a3866ff7acadd1064c 100644
--- a/src/trainer.py
+++ b/src/trainer.py
@@ -97,9 +97,11 @@ class Trainer():
                     self.ckp.log[-1, idx_data, idx_scale] += utility.calc_psnr(
                         sr, hr, scale, self.args.rgb_range, dataset=d
                     )
-                    if self.args.save_gt: save_list.extend([lr, hr])
+                    if self.args.save_gt:
+                        save_list.extend([lr, hr])
 
-                    self.ckp.save_results(d, filename[0], save_list, scale)
+                    if self.args.save_results:
+                        self.ckp.save_results(d, filename[0], save_list, scale)
 
                 self.ckp.log[-1, idx_data, idx_scale] /= len(d)
                 best = self.ckp.log.max(0)