Update app.py

app.py

@@ -102,8 +102,8 @@ def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str
     return p.replace("{prompt}", positive), n + negative
 
 def load_and_prepare_model():
-    vaeX = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None,use_safetensors=False,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)
+    vaeX = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None,use_safetensors=False,torch_dtype=torch.float32,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)
     pipe = StableDiffusionXLPipeline.from_pretrained(
         #'John6666/uber-realistic-porn-merge-ponyxl-urpm-ponyxlhybridv1-sdxl',
         #'John6666/uber-realistic-porn-merge-xl-urpmxl-v3-sdxl',
@@ -138,7 +138,7 @@ def load_and_prepare_model():
     pipe.vae = vaeX #.to(torch.bfloat16)
     #****  NEVER TO BFLOAT BEFORE CUDA****#
 
-    #pipe.vae.force_upcast
+    #pipe.vae.force_upcast=True
 
     pipe.scheduler = sched
     # pipe.load_lora_weights("ford442/sdxl-vae-bf16", weight_name="LoRA/Fantasy_World_XL.safetensors", adapter_name="fantasy")