Update app.py

app.py

@@ -39,8 +39,8 @@ torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction = False
 torch.backends.cudnn.allow_tf32 = False
 torch.backends.cudnn.deterministic = False
 torch.backends.cudnn.benchmark = False
-#torch.backends.cuda.preferred_blas_library="cublas"
-# torch.backends.cuda.preferred_linalg_library="cusolver"
+torch.backends.cuda.preferred_blas_library="cublas"
+torch.backends.cuda.preferred_linalg_library="cusolver"
 torch.set_float32_matmul_precision("highest")
 
 FTP_HOST = 'noahcohn.com'
@@ -123,7 +123,7 @@ def load_and_prepare_model():
         #torch_dtype=torch.bfloat16,
         add_watermarker=False,
        # custom_pipeline="lpw_stable_diffusion_xl",
-        #use_safetensors=True,
+        use_safetensors=True,
         token=HF_TOKEN,
         text_encoder=None,
         text_encoder_2=None,
@@ -601,14 +601,14 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
                 minimum=448,
                 maximum=MAX_IMAGE_SIZE,
                 step=64,
-                value=768,
+                value=1024,
             )
             height = gr.Slider(
                 label="Height",
                 minimum=448,
                 maximum=MAX_IMAGE_SIZE,
                 step=64,
-                value=768,
+                value=1024,
             )
         with gr.Row():
             guidance_scale = gr.Slider(
@@ -616,14 +616,14 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
                 minimum=0.1,
                 maximum=30,
                 step=0.1,
-                value=3.8,
+                value=3.75,
             )
             num_inference_steps = gr.Slider(
                 label="Number of inference steps",
                 minimum=10,
                 maximum=1000,
                 step=10,
-                value=170,
+                value=200,
             )
 
     gr.Examples(