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import spaces | |
import gradio as gr | |
from wtpsplit import SaT | |
# Initialize the SaT model | |
# We use 'sat-3l-sm' as it's recommended for general sentence segmentation tasks | |
# and offers a good balance between speed and performance | |
sat = SaT("sat-3l-sm") | |
sat.half().to("cuda") | |
def segment_text(input_text): | |
# Use the SaT model to split the input text into sentences | |
sentences = sat.split(input_text) | |
# Join the sentences with newlines for better readability in the output | |
return "\n".join(sentences) | |
# Create the Gradio interface | |
iface = gr.Interface( | |
fn=segment_text, | |
inputs=gr.Textbox(lines=5, label="Input Text"), | |
outputs=gr.Textbox(lines=10, label="Segmented Text"), | |
title="Text Segmentation with SaT", | |
description="This app uses the SaT (Segment any Text) model to split input text into sentences.", | |
examples=[ | |
["This is a test This is another test."], | |
["Hello this is a test But this is different now Now the next one starts looool"], | |
["The quick brown fox jumps over the lazy dog It was the best of times, it was the worst of times"], | |
] | |
) | |
# Launch the app | |
iface.launch() |