Update app.py

app.py

@@ -18,7 +18,7 @@ pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
 pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
+MAX_IMAGE_SIZE = 1440
 
 @spaces.GPU(duration=65)
 def infer(
@@ -28,8 +28,8 @@ def infer(
     randomize_seed=False,
     width=1024,
     height=1024,
-    guidance_scale=4.5,
-    num_inference_steps=40,
+    guidance_scale=3,
+    num_inference_steps=20,
     progress=gr.Progress(track_tqdm=True),
 ):
     if randomize_seed:
@@ -63,8 +63,7 @@ css = """
 
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # [Stable Diffusion 3.5 Large (8B)](https://huggingface.co/stabilityai/stable-diffusion-3.5-large)")
-        gr.Markdown("[Learn more](https://stability.ai/news/introducing-stable-diffusion-3-5) about the Stable Diffusion 3.5 series. Try on [Stability AI API](https://platform.stability.ai/docs/api-reference#tag/Generate/paths/~1v2beta~1stable-image~1generate~1sd3/post), or [download model](https://huggingface.co/stabilityai/stable-diffusion-3.5-large) to run locally with ComfyUI or diffusers.")
+        gr.Markdown(" # [Stable Diffusion 3.5 Medium Turbo")
         with gr.Row():
             prompt = gr.Text(
                 label="Prompt",
@@ -119,7 +118,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=0.0,
                     maximum=7.5,
                     step=0.1,
-                    value=4.5,
+                    value=3,
                 )
 
                 num_inference_steps = gr.Slider(
@@ -127,7 +126,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=40, 
+                    value=20,
                 )
 
         gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=infer, cache_examples=True, cache_mode="lazy")