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import gradio as gr | |
from span_marker import SpanMarkerModel | |
# Download the model from the Hugging Face Hub | |
model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-bert-base-acronyms") | |
# Define the function for prediction | |
def predict_acronyms(text): | |
if text: | |
output = model.predict(text) | |
return output | |
return {"error": "Please provide valid text"} | |
# Create the Gradio interface | |
interface = gr.Interface( | |
fn=predict_acronyms, | |
inputs=gr.Textbox(label="Enter some text:", lines=5, placeholder="Type here..."), | |
outputs=gr.JSON(label="Predicted Output"), | |
title="Acronym Detection with Span Marker", | |
description="This application detects acronyms in the given text using the SpanMarker model." | |
) | |
# Launch the Gradio app | |
if __name__ == "__main__": | |
interface.launch() |