Update app.py

app.py

@@ -113,7 +113,7 @@ def load_and_prepare_model(model_id):
     pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0")
     pipe = StableDiffusionXLPipeline.from_pretrained(
         model_id,
-     #  torch_dtype=torch.bfloat16,
+        torch_dtype=torch.bfloat16,
         add_watermarker=False,
         use_safetensors=True,
      #  vae=AutoencoderKL.from_pretrained("BeastHF/MyBack_SDXL_Juggernaut_XL_VAE/MyBack_SDXL_Juggernaut_XL_VAE_V10(version_X).safetensors",repo_type='model',safety_checker=None),
@@ -126,9 +126,9 @@ def load_and_prepare_model(model_id):
 
     pipe.unet = pipeX.unet
     #pipe.to(dtype=torch.bfloat16)
-    #pipe.to(device)
-    #pipe.to(torch.bfloat16)
-    pipe.to(device, torch.bfloat16)
+    pipe.to(device)
+    pipe.to(torch.bfloat16)
+    #pipe.to(device, torch.bfloat16)
     del pipeX
     #sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", algorithm_type="dpmsolver++")
     #sched = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, beta_schedule="linear", algorithm_type="dpmsolver++")
@@ -209,12 +209,11 @@ def generate_30(
         f.write(f"Steps: {num_inference_steps} \n")
         f.write(f"Guidance Scale: {guidance_scale} \n")
         f.write(f"SPACE SETUP: \n")
-        f.write(f"Use Safetensors: no \n")
-        f.write(f"Use Model Dtype: no \n")
+        f.write(f"Use Safetensors: True \n")
+        f.write(f"Use Model Dtype: yes \n")
         f.write(f"Model Scheduler: Euler_a custom \n")
         f.write(f"Model VAE: stabilityai/sdxl-vae no dtype \n")
         f.write(f"Model UNET: stabilityai no dtype \n")
-        f.write(f"Model to cuda/dtype \n")
     upload_to_ftp(filename) 
     for i in range(0, num_images, BATCH_SIZE):
         batch_options = options.copy()
@@ -276,12 +275,11 @@ def generate_60(
         f.write(f"Steps: {num_inference_steps} \n")
         f.write(f"Guidance Scale: {guidance_scale} \n")
         f.write(f"SPACE SETUP: \n")
-        f.write(f"Use Safetensors: no \n")
-        f.write(f"Use Model Dtype: no \n")
+        f.write(f"Use Safetensors: True \n")
+        f.write(f"Use Model Dtype: yes \n")
         f.write(f"Model Scheduler: Euler_a custom \n")
         f.write(f"Model VAE: stabilityai/sdxl-vae no dtype \n")
         f.write(f"Model UNET: stabilityai no dtype \n")
-        f.write(f"Model to cuda/dtype \n")
     upload_to_ftp(filename) 
     for i in range(0, num_images, BATCH_SIZE):
         batch_options = options.copy()
@@ -343,12 +341,11 @@ def generate_90(
         f.write(f"Steps: {num_inference_steps} \n")
         f.write(f"Guidance Scale: {guidance_scale} \n")
         f.write(f"SPACE SETUP: \n")
-        f.write(f"Use Safetensors: no \n")
-        f.write(f"Use Model Dtype: no \n")
+        f.write(f"Use Safetensors: True \n")
+        f.write(f"Use Model Dtype: yes \n")
         f.write(f"Model Scheduler: Euler_a custom \n")
         f.write(f"Model VAE: stabilityai/sdxl-vae no dtype \n")
         f.write(f"Model UNET: stabilityai no dtype \n")
-        f.write(f"Model to cuda/dtype \n")
     upload_to_ftp(filename) 
     for i in range(0, num_images, BATCH_SIZE):
         batch_options = options.copy()