Update app.py

app.py

@@ -28,40 +28,7 @@ pipe_schnell = DiffusionPipeline.from_pretrained(
     torch_dtype=torch.bfloat16
 )
 
-@spaces.GPU
-def run_dev_hyper(prompt):
-    print("dev_hyper")
-    pipe_dev.to("cuda")
-    print(hyper_lora)
-    pipe_dev.load_lora_weights(hyper_lora)
-    print("Loaded hyper lora!")
-    image = pipe_dev(prompt, num_inference_steps=8, joint_attention_kwargs={"scale": 0.125}).images[0]
-    print("Ran!")
-    pipe_dev.unload_lora_weights()
-    return image
-
-@spaces.GPU
-def run_dev_turbo(prompt):
-    print("dev_turbo")
-    pipe_dev.to("cuda")
-    print(turbo_lora)
-    pipe_dev.load_lora_weights(turbo_lora)
-    print("Loaded turbo lora!")
-    image = pipe_dev(prompt, num_inference_steps=8).images[0]
-    print("Ran!")
-    pipe_dev.unload_lora_weights()
-    return image
-
-@spaces.GPU
-def run_schnell(prompt):
-    print("schnell")
-    pipe_schnell.to("cuda")
-    print("schnell on gpu")
-    image = pipe_schnell(prompt, num_inference_steps=4).images[0]
-    print("Ran!")
-    return image
-
-@spaces.GPU
+@spaces.GPU(duration=75)
 def run_parallel_models(prompt):
     pipe_dev.load_lora_weights(hyper_lora)
     image = pipe_dev(prompt, num_inference_steps=8, joint_attention_kwargs={"scale": 0.125}).images[0]