diff --git a/library/train_util.py b/library/train_util.py
index 415f9b70..1a42d591 100644
--- a/library/train_util.py
+++ b/library/train_util.py
@@ -1423,7 +1423,9 @@ def add_training_arguments(parser: argparse.ArgumentParser, support_dreambooth:
                       help="Number of steps for the warmup in the lr scheduler (default is 0) / 学習率のスケジューラをウォームアップするステップ数（デフォルト0）")
   parser.add_argument("--noise_offset", type=float, default=None,
                       help="enable noise offset with this value (if enabled, around 0.1 is recommended) / Noise offsetを有効にしてこの値を設定する（有効にする場合は0.1程度を推奨）")
-
+  parser.add_argument("--lowram", action="store_true",
+                      help="load models to VRAM instead of RAM (for machines which have bigger VRAM than RAM such as Colab and Kaggle)")
+  
   if support_dreambooth:
     # DreamBooth training
     parser.add_argument("--prior_loss_weight", type=float, default=1.0,
diff --git a/train_network.py b/train_network.py
index 5983a7ef..e29e0174 100644
--- a/train_network.py
+++ b/train_network.py
@@ -156,9 +156,10 @@ def train(args):
 
   # モデルを読み込む
   text_encoder, vae, unet, _ = train_util.load_target_model(args, weight_dtype)
-  # unnecessary, but work on low-ram device
-  text_encoder.to("cuda")
-  unet.to("cuda")
+  # work on low-ram device
+  if args.lowram:
+    text_encoder.to("cuda")
+    unet.to("cuda")
   # モデルに xformers とか memory efficient attention を組み込む
   train_util.replace_unet_modules(unet, args.mem_eff_attn, args.xformers)