Update app.py

app.py

@@ -115,8 +115,8 @@ def load_and_prepare_model():
     #unetX = UNet2DConditionModel.from_pretrained('ford442/RealVisXL_V5.0_BF16',subfolder='unet').to(torch.bfloat16)   #  ,use_safetensors=True  FAILS
     #sched = EulerAncestralDiscreteScheduler.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='scheduler',beta_schedule="scaled_linear", steps_offset=1,timestep_spacing="trailing"))
     #sched = EulerAncestralDiscreteScheduler.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='scheduler', steps_offset=1,timestep_spacing="trailing")
-    #sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1,use_karras_sigmas=True)
-    sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear",token=HF_TOKEN)
+    sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16',token=HF_TOKEN, subfolder='scheduler',beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1) #,use_karras_sigmas=True)
+    #sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16',token=HF_TOKEN, subfolder='scheduler',beta_schedule="scaled_linear")
     #sched = DPMSolverSDEScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler')
     #pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0").to(torch.bfloat16)
     #pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",use_safetensors=True)
@@ -278,7 +278,7 @@ def generate_30(
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
     torch.set_default_device('cuda')
-    pipe.set_adapters(["skin"], adapter_weights=[lora_scale])
+    #pipe.set_adapters(["skin"], adapter_weights=[lora_scale])
     seed = int(randomize_seed_fn())
     generator = torch.Generator(device='cuda').manual_seed(seed)
     #prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
@@ -333,8 +333,8 @@ def generate_60(
     lora_scale: float = 0.5,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
-    torch.set_default_device('cuda')
-    pipe.set_adapters(["skin"], adapter_weights=[lora_scale])
+    #torch.set_default_device('cuda')
+    #pipe.set_adapters(["skin"], adapter_weights=[lora_scale])
     seed = int(randomize_seed_fn())
     generator = torch.Generator(device='cuda').manual_seed(seed)
     #prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
@@ -389,8 +389,8 @@ def generate_90(
     lora_scale: float = 0.5,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
-    torch.set_default_device('cuda')
-    pipe.set_adapters(["skin"], adapter_weights=[lora_scale])
+    #torch.set_default_device('cuda')
+    #pipe.set_adapters(["skin"], adapter_weights=[lora_scale])
     seed = int(randomize_seed_fn())
     generator = torch.Generator(device='cuda').manual_seed(seed)
     #prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)