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import gradio as gr
from transformers import pipeline
# Laden des Modells für Masked Language Modeling
unmasker = pipeline('fill-mask', model='bert-base-uncased')
# Gradio Interface
def masked_language_modeling(text):
results = unmasker(text)
return results[0]['sequence']
iface = gr.Interface(
fn=masked_language_modeling,
inputs=gr.Textbox(),
outputs=gr.Textbox(),
title='BERT Masked Language Modeling',
description='Enter a sentence with a [MASK] and see the predictions.'
)
# Starte die Gradio Benutzeroberfläche
if __name__ == '__main__':
iface.launch()
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