| import gradio as gr | |
| from transformers import pipeline | |
| fill_mask = pipeline("fill-mask", model="bert-base-uncased") | |
| def complete_sentence(text): | |
| if "[MASK]" not in text: | |
| return "Please include [MASK] token in your input text" | |
| results = fill_mask(text) | |
| output = [] | |
| for result in results: | |
| completed = f"Token: {result['token_str']} (Score: {result['score']:.3f})" | |
| output.append(completed) | |
| return "\n".join(output) | |
| iface = gr.Interface( | |
| fn=complete_sentence, | |
| inputs=gr.Textbox( | |
| lines=3, | |
| placeholder="Enter text with [MASK] token...", | |
| label="Input Text" | |
| ), | |
| outputs=gr.Textbox( | |
| lines=5, | |
| label="Completed Sentences" | |
| ), | |
| title="Sentence Completion", | |
| description="Enter a sentence with [MASK] token and get predictions for the masked word", | |
| examples=[ | |
| ["The [MASK] is bright today."], | |
| ["I love to [MASK] in my free time."], | |
| ["She [MASK] to the store yesterday."] | |
| ], | |
| theme=gr.themes.Soft() | |
| ) | |
| iface.launch() | |
| if __name__ == '__main__': | |
| demo.launch() |