Update app.py

app.py

@@ -108,7 +108,7 @@ def load_and_prepare_model(model_id):
     model_dtypes = {"ford442/RealVisXL_V5.0_BF16": torch.bfloat16,}
     dtype = model_dtypes.get(model_id, torch.bfloat16)  # Default to float32 if not found
     #vaeX = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", safety_checker=None, use_safetensors=False)
-    vaeX = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None, use_safetensors=False,scaling_factor= 0.1821501)
+    vaeX = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None, use_safetensors=False)
     #vae = AutoencoderKL.from_pretrained('cross-attention/asymmetric-autoencoder-kl-x-2',use_safetensors=False)
     #vae = AutoencoderKL.from_single_file('https://huggingface.co/ford442/sdxl-vae-bf16/mySLR/myslrVAE_v10.safetensors')
     #vaeX = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse",use_safetensors=True)
@@ -119,7 +119,7 @@ def load_and_prepare_model(model_id):
     #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('SG161222/RealVisXL_V5.0', 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", beta_start=0.00085, beta_end=0.012, steps_offset=1,use_karras_sigmas=True)    #pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0").to(torch.bfloat16)
+    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,timestep_spacing="trailing")    #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(
@@ -222,8 +222,8 @@ def uploadNote():
         f.write(f"Guidance Scale: {guidance_scale} \n")
         f.write(f"SPACE SETUP: \n")
         f.write(f"Use Model Dtype: no \n")
-        f.write(f"Model Scheduler: Euler_a all_custom before cuda \n")
-        f.write(f"Model VAE: sdxl-vae ,scaling_factor= 0.1821501 to bfloat with cuda then attn_proc \n")
+        f.write(f"Model Scheduler: Euler_a all_custom before cuda woth trailing \n")
+        f.write(f"Model VAE: sdxl-vae  to bfloat with cuda then attn_proc \n")
         f.write(f"Model UNET: default  to bfloat with cuda then attn_proc \n")
         f.write(f"Model HiDiffusion OFF \n")
         f.write(f"Model do_resize OFF \n")