Update app.py

app.py

@@ -1,18 +1,20 @@
 import gradio as gr
 import numpy as np
 import random
-from diffusers import DiffusionPipeline
+from diffusers.models.modeling_outputs import Transformer2DModelOutput
 import torch
 
+
+
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 if torch.cuda.is_available():
     torch.cuda.max_memory_allocated(device=device)
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", token=hf_token, torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+    pipe = Transformer2DModelOutput("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
     pipe.enable_xformers_memory_efficient_attention()
     pipe = pipe.to(device)
 else: 
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", token=hf_token, use_safetensors=True)
+    pipe = Transformer2DModelOutput("stabilityai/stable-diffusion-3-medium-diffusers", use_safetensors=True)
     pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max