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()