| 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() | |