Update app.py

app.py

@@ -11,16 +11,16 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 device = "cuda"
 dtype = torch.float16
 
-repo = "stabilityai/stable-diffusion-3-medium"
+repo = "stabilityai/stable-diffusion-3.5-large"
 t2i = StableDiffusion3Pipeline.from_pretrained(repo, torch_dtype=torch.float16, revision="refs/pr/26",token=os.environ["TOKEN"]).to(device)
 
 model = AutoModelForCausalLM.from_pretrained(
-    "microsoft/Phi-3-mini-4k-instruct", 
+    "microsoft/Phi-3.5-mini-instruct", 
     device_map="cuda", 
     torch_dtype=torch.bfloat16, 
     trust_remote_code=True, 
 )
-tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
+tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3.5-mini-instruct")
 upsampler = pipeline(
     "text-generation",
     model=model,
@@ -88,7 +88,7 @@ with gr.Blocks(css=css) as demo:
     
     with gr.Column(elem_id="col-container"):
         gr.Markdown(f"""
-        # 日本語が入力できる SD3 Medium
+        # 日本語が入力できる SD3.5 Large
         """)
         
         with gr.Row():
@@ -131,7 +131,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=64,
-                    value=1024,
+                    value=1024+512,
                 )
                 
                 height = gr.Slider(
@@ -139,7 +139,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=64,
-                    value=1024,
+                    value=1024+512,
                 )
             
             with gr.Row():
@@ -149,7 +149,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
-                    value=5.0,
+                    value=3.5,
                 )
                 
                 num_inference_steps = gr.Slider(