Update app.py

app.py

@@ -12,7 +12,6 @@ import warnings
 warnings.filterwarnings("ignore")
 from PIL import Image
 import numpy as np
-from utils import load_models
 from editing import get_direction, debias
 from lora_w2w import LoRAw2w
 from huggingface_hub import snapshot_download
@@ -56,7 +55,7 @@ df = torch.load(f"{models_path}/files/identity_df.pt")
 weight_dimensions = torch.load(f"{models_path}/files/weight_dimensions.pt")
 pinverse = torch.load(f"{models_path}/files/pinverse_1000pc.pt", map_location=torch.device('cpu')).bfloat16().to(device.value)
 
-unet.value, vae.value, text_encoder.value, tokenizer.value, noise_scheduler.value = load_models(device.value)
+unet.value, vae.value, text_encoder.value, tokenizer.value, noise_scheduler.value = load_models()
 
 young = gr.State()
 young.value = get_direction(df, "Young", pinverse, 1000, device.value)
@@ -168,7 +167,7 @@ def sample_weights(unet, proj, mean, std, v, device, factor = 1.0):
 @torch.no_grad()
 @spaces.GPU
 def sample_model():
-    unet.value, _, _, _, _ = load_models(device.value)
+    unet.value, _, _, _, _ = load_models()
     network.value = sample_weights(unet.value, proj, mean, std, v[:, :1000], device.value, factor = 1.00)
  
 @torch.no_grad()