Upload app.py

app.py

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+import gradio as gr
+import torch
+from diffusers import AutoPipelineForText2Image
+
+pipe = AutoPipelineForText2Image.from_pretrained(
+    "stabilityai/sdxl-turbo",
+    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
+    variant="fp16" if torch.cuda.is_available() else None,
+)
+pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")
+
+def generate_image(prompt):
+    result = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0)
+    return result.images[0]  # returns a PIL image
+
+iface = gr.Interface(
+    fn=generate_image,
+    inputs=gr.Textbox(label="Prompt"),
+    outputs=gr.Image(type="pil", format="jpeg"),  # base64 encoded image
+    title="Speech2Image - Turbo",
+    description="Fast image gen using SDXL Turbo"
+)
+
+if __name__ == "__main__":
+    iface.launch()
+
+