Update merged_files3.py

merged_files3.py

@@ -181,38 +181,30 @@ t5_path = hf_hub_download(repo_id="comfyanonymous/flux_text_encoders", filename=
 sd15_name = 'stablediffusionapi/realistic-vision-v51'
 tokenizer = CLIPTokenizer.from_pretrained(sd15_name, subfolder="tokenizer")
 
-# Load models in sequence with memory clearing between loads
-@spaces.GPU(duration=60)
-@torch.inference_mode()
-def load_models():
-    clear_memory()
-    
-    global text_encoder, vae, unet, rmbg
-    
-    # Load text encoder
-    text_encoder = CLIPTextModel.from_pretrained(sd15_name, subfolder="text_encoder")
-    text_encoder = text_encoder.to(device=device, dtype=dtype)
-    clear_memory()
-    
-    # Load VAE
-    vae = AutoencoderKL.from_pretrained(sd15_name, subfolder="vae")
-    vae = vae.to(device=device, dtype=dtype)
-    clear_memory()
-    
-    # Load UNet
-    unet = UNet2DConditionModel.from_pretrained(sd15_name, subfolder="unet")
-    unet = unet.to(device=device, dtype=dtype)
-    clear_memory()
-    
-    # Load RMBG
-    rmbg = AutoModelForImageSegmentation.from_pretrained(
-        "ZhengPeng7/BiRefNet", trust_remote_code=True
-    )
-    rmbg = rmbg.to(device=device, dtype=torch.float32)
-    clear_memory()
 
-# Call load_models after device setup
-load_models()
+# Load text encoder
+text_encoder = CLIPTextModel.from_pretrained(sd15_name, subfolder="text_encoder")
+text_encoder = text_encoder.to(device=device, dtype=dtype)
+clear_memory()
+
+# Load VAE
+vae = AutoencoderKL.from_pretrained(sd15_name, subfolder="vae")
+vae = vae.to(device=device, dtype=dtype)
+clear_memory()
+
+# Load UNet
+unet = UNet2DConditionModel.from_pretrained(sd15_name, subfolder="unet")
+unet = unet.to(device=device, dtype=dtype)
+clear_memory()
+
+# Load RMBG
+rmbg = AutoModelForImageSegmentation.from_pretrained(
+    "ZhengPeng7/BiRefNet", trust_remote_code=True
+)
+rmbg = rmbg.to(device=device, dtype=torch.float32)
+clear_memory()
+
+
 
 from diffusers import FluxTransformer2DModel, FluxFillPipeline, GGUFQuantizationConfig
 from transformers import T5EncoderModel