Update app.py

app.py

@@ -119,13 +119,13 @@ def load_and_prepare_model(model_id):
     #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('SG161222/RealVisXL_V5.0', subfolder='scheduler')
-    pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0").to(torch.bfloat16)
+    #pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0").to(torch.bfloat16)
     #pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",use_safetensors=True)
     
     pipe = StableDiffusionXLPipeline.from_pretrained(
-        'ford442/RealVisXL_V5.0_BF16',
+        #'ford442/RealVisXL_V5.0_BF16',
     #    'ford442/Juggernaut-XI-v11-fp32',
-        #'SG161222/RealVisXL_V5.0',
+        'SG161222/RealVisXL_V5.0',
         #torch_dtype=torch.bfloat16,
         add_watermarker=False,
        # custom_pipeline="lpw_stable_diffusion_xl",
@@ -147,7 +147,7 @@ def load_and_prepare_model(model_id):
     pipe.vae.do_resize=False
     pipe.scheduler = sched
     #pipe.vae=vae.to(torch.bfloat16)
-    pipe.unet=pipeX.unet
+    #pipe.unet=pipeX.unet
     #pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
 
     pipe.to(device)