Create app.py

app.py

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+import gradio as gr
+from diffusers import AutoPipelineForText2Image
+import torch
+
+# Function to generate the image
+def generate_image(prompt):
+    # Load the pipeline with default settings which should default to a CPU compatible setting if `fp32` is available
+    pipe = AutoPipelineForText2Image.from_pretrained(
+        "stabilityai/sdxl-turbo",
+        torch_dtype=torch.float32  # Using float32 for CPU compatibility
+    )
+    pipe = pipe.to("cpu")  # Ensure the pipeline is using the CPU
+
+    # Generate the image based on the prompt
+    image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
+    return image
+
+# Define the Gradio interface
+interface = gr.Interface(
+    fn=generate_image,
+    inputs=gr.Textbox(label="Enter a description for the image"),
+    outputs=gr.Image(type="pil", label="Generated Image"),
+    title="Image Generator",
+    description="This interface generates images based on your descriptions using the Stability AI SDXL-Turbo model."
+)
+
+# Prepare to run in Hugging Face Spaces
+if __name__ == "__main__":
+    interface.launch()