Update app.py

app.py

@@ -110,11 +110,11 @@ model_repo='John6666/uber-realistic-porn-merge-xl-urpmxl-v6final-sdxl'
 
 rv='ford442/RealVisXL_V5.0_BF16'
     
-text_encoder = CLIPTextModel.from_pretrained(rv, low_cpu_mem_usage=False, subfolder='text_encoder', token=True)#.to(device=device, dtype=torch.bfloat16)
-text_encoder_2 = CLIPTextModelWithProjection.from_pretrained(model_repo, low_cpu_mem_usage=False, subfolder='text_encoder_2',token=True)#.to(device=device, dtype=torch.bfloat16)
-tokenizer_1 = CLIPTokenizer.from_pretrained(rv, low_cpu_mem_usage=False, subfolder='tokenizer', token=True)
-tokenizer_2 = CLIPTokenizer.from_pretrained(model_repo, low_cpu_mem_usage=False, subfolder='tokenizer_2', token=True)
-scheduler = EulerAncestralDiscreteScheduler.from_pretrained(rv, low_cpu_mem_usage=False, subfolder='scheduler', token=True)
+text_encoder = CLIPTextModel.from_pretrained(rv, subfolder='text_encoder', token=True)#.to(device=device, dtype=torch.bfloat16)
+text_encoder_2 = CLIPTextModelWithProjection.from_pretrained(model_repo, subfolder='text_encoder_2',token=True)#.to(device=device, dtype=torch.bfloat16)
+tokenizer_1 = CLIPTokenizer.from_pretrained(rv, subfolder='tokenizer', token=True)
+tokenizer_2 = CLIPTokenizer.from_pretrained(model_repo, subfolder='tokenizer_2', token=True)
+scheduler = EulerAncestralDiscreteScheduler.from_pretrained(rv, subfolder='scheduler', token=True)
 vaeXL = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", low_cpu_mem_usage=False, safety_checker=None, use_safetensors=False, torch_dtype=torch.float32, token=True) #.to(device).to(torch.bfloat16) #.to(device=device, dtype=torch.bfloat16)
 unet = UNet2DConditionModel.from_pretrained(model_repo, low_cpu_mem_usage=False, subfolder='unet', upcast_attention=True, attention_type='gated-text-image', token=True)
 
@@ -130,17 +130,17 @@ def load_and_prepare_model():
         token=True,
         text_encoder=None,
         text_encoder_2=None,
-        tokenizer=None,
-        tokenizer_2=None,
-        scheduler=None,
-        unet=None,
+        #tokenizer=None,
+        #tokenizer_2=None,
+        #scheduler=None,
+        unet=unet,
         vae=None,
     )
    
-    pipe.scheduler=scheduler
-    pipe.tokenizer=tokenizer_1
-    pipe.tokenizer_2=tokenizer_2
-    pipe.unet=unet
+    #pipe.scheduler=scheduler
+    #pipe.tokenizer=tokenizer_1
+    #pipe.tokenizer_2=tokenizer_2
+    #pipe.unet=unet
     '''
     scaling_factor (`float`, *optional*, defaults to 0.18215):
             The component-wise standard deviation of the trained latent space computed using the first batch of the