sending app.py

app.py

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+import gradio as gr
+from diffusers import DiffusionPipeline
+import torch
+
+# Initialize the model pipeline
+pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", 
+                                         torch_dtype=torch.float16, 
+                                         use_safetensors=True, 
+                                         variant="fp16")
+
+pipe.to("cuda" if torch.cuda.is_available() else "cpu")
+
+# Define the inference function
+def generate_image(prompt):
+    image = pipe(prompt).images[0]
+    return image
+
+# Create the Gradio interface
+iface = gr.Interface(fn=generate_image, inputs="text", outputs="image", live=True)
+
+# Launch the Gradio app
+iface.launch()

requirements.txt

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+diffusers
+torch
+gradio