Update app.py

app.py

@@ -225,19 +225,12 @@ MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 4096
 
 if torch.cuda.is_available():
-    vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
-    pipe = AutoPipelineForText2Image.from_pretrained(
-        "Menyu/noobaiXLNAIXL_vPred065SVersion",
-        vae=vae,
-        torch_dtype=torch.float16,
-        use_safetensors=True,
-        add_watermarker=False
-    )
-    pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
-    pipe.scheduler.register_to_config(
-        prediction_type="v_prediction",
-        rescale_betas_zero_snr=True,
+    pipe = StableDiffusionXLPipeline.from_pretrained(
+        "Menyu/noobaiXLNAIXL_vPred10Version",
+        torch_dtype=torch.float16
     )
+    scheduler_args = {"prediction_type": "v_prediction", "rescale_betas_zero_snr": True}
+    pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, **scheduler_args)
     pipe.to("cuda")
 
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
@@ -306,7 +299,7 @@ footer {
 
 with gr.Blocks(css=css) as demo:
     gr.Markdown("""# 梦羽的模型生成器
-        ### 快速生成NoobAIXL V预测0.65s版本的模型图片""")
+        ### 快速生成NoobAIXL V预测1.0版本的模型图片""")
     with gr.Group():
         with gr.Row():
             prompt = gr.Text(