Update app.py

app.py

@@ -1,30 +1,6 @@
 import gradio as gr
-import torch
-from transformers import pipeline
 
-# Load your model pipeline (e.g., text generation or similar tasks)
-model = pipeline("text-generation", model="black-forest-labs/FLUX.1-schnell")
+with gr.Blocks() as demo:
+    gr.load("black-forest-labs/FLUX.1-dev", src="spaces")
 
-# Define a function that includes parameters
-def generate_text(prompt, seed, num_inference_steps):
-    # Set the random seed for reproducibility
-    generator = torch.manual_seed(seed)
-    
-    # Generate text with additional parameters
-    output = model(prompt, num_return_sequences=1, max_length=256, 
-                   do_sample=True, generator=generator)
-    return output[0]['generated_text']
-
-# Create a Gradio interface
-interface = gr.Interface(
-    fn=generate_text,
-    inputs=[
-        gr.Textbox(label="Input Prompt"),
-        gr.Number(label="Seed", default=0),
-        gr.Number(label="Inference Steps", default=50)
-    ],
-    outputs=gr.Textbox(label="Generated Text")
-)
-
-# Launch the interface
-interface.launch()
+demo.launch()