diff --git a/inference_gfpgan_full.py b/inference_gfpgan_full.py
index 1b764157..07b3d5a8 100644
--- a/inference_gfpgan_full.py
+++ b/inference_gfpgan_full.py
@@ -19,7 +19,8 @@ def restoration(gfpgan,
                 has_aligned=False,
                 only_center_face=True,
                 suffix=None,
-                paste_back=False):
+                paste_back=False,
+                device='cuda'):
     # read image
     img_name = os.path.basename(img_path)
     print(f'Processing {img_name} ...')
@@ -43,7 +44,7 @@ def restoration(gfpgan,
         # prepare data
         cropped_face_t = img2tensor(cropped_face / 255., bgr2rgb=True, float32=True)
         normalize(cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True)
-        cropped_face_t = cropped_face_t.unsqueeze(0).to('cuda')
+        cropped_face_t = cropped_face_t.unsqueeze(0).to(device)
 
         try:
             with torch.no_grad():
@@ -77,17 +78,18 @@ def restoration(gfpgan,
 
 if __name__ == '__main__':
     device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+
     parser = argparse.ArgumentParser()
 
-    parser.add_argument('--upscale_factor', type=int, default=1)
+    parser.add_argument('--upscale_factor', type=int, default=2)
     parser.add_argument('--arch', type=str, default='clean')
     parser.add_argument('--channel', type=int, default=2)
-    parser.add_argument('--model_path', type=str, default='experiments/pretrained_models/GFPGANv1.pth')
+    parser.add_argument('--model_path', type=str, default='experiments/pretrained_models/GFPGANCleanv1-NoCE-C2.pth')
     parser.add_argument('--test_path', type=str, default='inputs/whole_imgs')
     parser.add_argument('--suffix', type=str, default=None, help='Suffix of the restored faces')
     parser.add_argument('--only_center_face', action='store_true')
     parser.add_argument('--aligned', action='store_true')
-    parser.add_argument('--paste_back', action='store_true')
+    parser.add_argument('--paste_back', action='store_false')
     parser.add_argument('--save_root', type=str, default='results')
 
     args = parser.parse_args()
@@ -123,14 +125,17 @@ def restoration(gfpgan,
             narrow=1,
             sft_half=True)
 
-    gfpgan.to(device)
-    checkpoint = torch.load(args.model_path, map_location=lambda storage, loc: storage)
-    gfpgan.load_state_dict(checkpoint['params_ema'])
-    gfpgan.eval()
+    gfpgan.load_state_dict(torch.load(args.model_path, map_location=lambda storage, loc: storage)['params_ema'])
+    gfpgan.to(device).eval()
 
     # initialize face helper
     face_helper = FaceRestoreHelper(
-        args.upscale_factor, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png')
+        args.upscale_factor,
+        face_size=512,
+        crop_ratio=(1, 1),
+        det_model='retinaface_resnet50',
+        save_ext='png',
+        device=device)
 
     img_list = sorted(glob.glob(os.path.join(args.test_path, '*')))
     for img_path in img_list:
@@ -142,6 +147,7 @@ def restoration(gfpgan,
             has_aligned=args.aligned,
             only_center_face=args.only_center_face,
             suffix=args.suffix,
-            paste_back=args.paste_back)
+            paste_back=args.paste_back,
+            device=device)
 
     print(f'Results are in the [{args.save_root}] folder.')