Update app.py

app.py

@@ -206,7 +206,7 @@ loras = [
 #--------------------------------------------------Model Initialization-----------------------------------------------------------------------------------------#
 
 dtype = torch.bfloat16
-device = "cuda" if torch.cuda.is_available() else "cpu"
+device = "cuda"
 base_model = "black-forest-labs/FLUX.1-dev"
 
 #TAEF1 is very tiny autoencoder which uses the same "latent API" as FLUX.1's VAE. FLUX.1 is useful for real-time previewing of the FLUX.1 generation process.#
@@ -302,7 +302,7 @@ def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps
     ).images[0]
     return final_image 
 
-@spaces.GPU(duration=100)
+@spaces.GPU()
 def run_lora(image_input, image_strength, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, lora_scale, prompt = "", progress=gr.Progress(track_tqdm=True)):
     if selected_index is None:
         raise gr.Error("You must select a LoRA before proceeding.🧨")