diff --git a/tools/convert_diffusers20_original_sd.py b/tools/convert_diffusers20_original_sd.py
index b9365b519..a6774328e 100644
--- a/tools/convert_diffusers20_original_sd.py
+++ b/tools/convert_diffusers20_original_sd.py
@@ -23,7 +23,7 @@ def convert(args):
     is_load_ckpt = os.path.isfile(args.model_to_load)
     is_save_ckpt = len(os.path.splitext(args.model_to_save)[1]) > 0
 
-    assert not is_load_ckpt or args.v1 != args.v2, f"v1 or v2 is required to load checkpoint / checkpointの読み込みにはv1/v2指定が必要です"
+    assert not is_load_ckpt or args.v1 != args.v2, "v1 or v2 is required to load checkpoint / checkpointの読み込みにはv1/v2指定が必要です"
     # assert (
     #     is_save_ckpt or args.reference_model is not None
     # ), f"reference model is required to save as Diffusers / Diffusers形式での保存には参照モデルが必要です"
@@ -37,7 +37,7 @@ def convert(args):
         text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoint(v2_model, args.model_to_load, unet_use_linear_projection_in_v2=args.unet_use_linear_projection)
     else:
         pipe = StableDiffusionPipeline.from_pretrained(
-            args.model_to_load, torch_dtype=load_dtype, tokenizer=None, safety_checker=None
+            args.model_to_load, torch_dtype=load_dtype, tokenizer=None, safety_checker=None, variant=args.variant
         )
         text_encoder = pipe.text_encoder
         vae = pipe.vae
@@ -57,7 +57,7 @@ def convert(args):
     if is_save_ckpt:
         original_model = args.model_to_load if is_load_ckpt else None
         key_count = model_util.save_stable_diffusion_checkpoint(
-            v2_model, args.model_to_save, text_encoder, unet, original_model, args.epoch, args.global_step, save_dtype, vae
+            v2_model, args.model_to_save, text_encoder, unet, original_model, args.epoch, args.global_step, None if args.metadata is None else eval(args.metadata), save_dtype=save_dtype, vae=vae
         )
         print(f"model saved. total converted state_dict keys: {key_count}")
     else:
@@ -65,7 +65,7 @@ def convert(args):
         model_util.save_diffusers_checkpoint(
             v2_model, args.model_to_save, text_encoder, unet, args.reference_model, vae, args.use_safetensors
         )
-        print(f"model saved.")
+        print("model saved.")
 
 
 def setup_parser() -> argparse.ArgumentParser:
@@ -99,6 +99,18 @@ def setup_parser() -> argparse.ArgumentParser:
     parser.add_argument(
         "--global_step", type=int, default=0, help="global_step to write to checkpoint / checkpointに記録するglobal_stepの値"
     )
+    parser.add_argument(
+        "--metadata",
+        type=str,
+        default=None,
+        help='metadata: metadata written in to the model in Python Dictionary. Example metadata: \'{"name": "model_name", "resolution": "512x512"}\'',
+    )
+    parser.add_argument(
+        "--variant",
+        type=str,
+        default=None,
+        help="variant: Diffusers variant to load. Example: fp16",
+    )
     parser.add_argument(
         "--reference_model",
         type=str,