diff --git a/library/model_util.py b/library/model_util.py
index 18489266..96c7bbf2 100644
--- a/library/model_util.py
+++ b/library/model_util.py
@@ -1089,6 +1089,11 @@ def save_diffusers_checkpoint(v2, output_dir, text_encoder, unet, pretrained_mod
 VAE_PREFIX = "first_stage_model."
 
 
+def convert_vae(vae_sd, vae_config):
+  converted_vae_checkpoint = convert_ldm_vae_checkpoint(vae_sd, vae_config)
+  vae = AutoencoderKL(**vae_config)
+  vae.load_state_dict(converted_vae_checkpoint)
+
 def load_vae(vae_id, dtype):
   print(f"load VAE: {vae_id}")
   if os.path.isdir(vae_id) or not os.path.isfile(vae_id):
@@ -1104,6 +1109,8 @@ def load_vae(vae_id, dtype):
   # local
   vae_config = create_vae_diffusers_config()
 
+  if vae_id.endswith(".bin"): return convert_vae(torch.load(vae_id, map_location="cpu"), vae_config)
+
   vae_model = (load_file(vae_id, "cpu") if is_safetensors(vae_id)
               else torch.load(vae_id, map_location="cpu"))
   vae_sd = vae_model['state_dict'] if 'state_dict' in vae_model else vae_model
@@ -1120,10 +1127,8 @@ def load_vae(vae_id, dtype):
     vae_sd = sd
     del sd
 
-  converted_vae_checkpoint = convert_ldm_vae_checkpoint(vae_sd, vae_config)
-  vae = AutoencoderKL(**vae_config)
-  vae.load_state_dict(converted_vae_checkpoint)
-  return vae
+  
+  return convert_vae(vae_sd, vae_config)
 
 
 # endregion