Update app.py

app.py

@@ -116,7 +116,7 @@ def load_and_prepare_model():
     #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")
+    sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear",token=HF_TOKEN)
     #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)
@@ -167,7 +167,7 @@ def load_and_prepare_model():
     
     #pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
     #pipe.scheduler = DPMSolverMultistepScheduler.from_pretrained('SG161222/RealVisXL_V5.0', subfolder='scheduler', algorithm_type='sde-dpmsolver++')
-    pipe.vae = vaeX.to(torch.bfloat16)
+    #pipe.vae = vaeX.to(torch.bfloat16)
     #pipe.unet = unetX
     
     #pipe.vae.do_resize=False
@@ -185,15 +185,15 @@ def load_and_prepare_model():
     pipe.vae.set_default_attn_processor()
     pipe.to(device, torch.bfloat16)
     
-    pipe.load_lora_weights("ford442/sdxl-vae-bf16", weight_name="LoRA/skin_texture_style_v4.safetensors", adapter_name="skin")
+    #pipe.load_lora_weights("ford442/sdxl-vae-bf16", weight_name="LoRA/skin_texture_style_v4.safetensors", adapter_name="skin")
     #pipe.unet.load_lora_adapter("ford442/sdxl-vae-bf16", weight_name="LoRA/skin_texture_style_v4.safetensors", prefix="unet")
     #pipe.text_encoder.load_lora_adapter("ford442/sdxl-vae-bf16", weight_name="LoRA/skin_texture_style_v4.safetensors", prefix="text_encoder")
     
-    pipe.unet = pipe.unet.to(memory_format=torch.contiguous_format)
+    #pipe.unet = pipe.unet.to(memory_format=torch.contiguous_format)
     
         #Some typical diffusers pipeline optimizations
-    # pipe.unet.to(memory_format=torch.channels_last) #Unsupported by hidet, but does not seem to make a difference if disabled.
-    #pipe.enable_vae_tiling()
+    pipe.unet.to(memory_format=torch.channels_last) #Unsupported by hidet, but does not seem to make a difference if disabled.
+    pipe.enable_vae_tiling()
     #pipe.enable_xformers_memory_efficient_attention()