Update app.py

app.py

@@ -80,7 +80,7 @@ HF_TOKEN = os.getenv("HF_TOKEN")
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
     
 def load_and_prepare_model():
-    vaeXL = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None, use_safetensors=False).to(device=device, dtype=torch.bfloat16)
+    vaeXL = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None, use_safetensors=False).to(device).to(torch.bfloat16) #.to(device=device, dtype=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)
     pipe = StableDiffusionXLPipeline.from_pretrained(
         'ford442/RealVisXL_V5.0_BF16',
@@ -91,7 +91,9 @@ def load_and_prepare_model():
     pipe.scheduler = sched
     pipe.vae.do_resize=False
     pipe.vae.vae_scale_factor=8
-    pipe.to(device=device, dtype=torch.bfloat16)
+    #pipe.to(device=device, dtype=torch.bfloat16)
+    pipe.to(device)
+    pipe.to(torch.bfloat16)
     pipe.vae.set_default_attn_processor()
     print(f'init noise scale: {pipe.scheduler.init_noise_sigma}')
     pipe.watermark=None
@@ -143,11 +145,8 @@ def uploadNote(prompt,num_inference_steps,guidance_scale,timestamp):
         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-bf16 before cuda then attn_proc / scale factor 8 \n")
-        f.write(f"Model UNET: sexy_beauty model \n")
-        f.write(f"Model HiDiffusion OFF \n")
-        f.write(f"Model do_resize ON \n")
-        f.write(f"added torch to prereq and changed accellerate  \n")
+        f.write(f"Model VAE: sdxl-vae \n")
+        f.write(f"To cuda then to bfloat \n")
     upload_to_ftp(filename) 
     
 @spaces.GPU(duration=30)