| import gradio as gr | |
| from transformers import pipeline | |
| BASE_MODEL = "nlpaueb/legal-bert-base-uncased" | |
| mask_filler = pipeline("fill-mask", model=BASE_MODEL) | |
| def mask_fill(text): | |
| k = [] | |
| preds = mask_filler(text) | |
| for pred in preds: | |
| k.append(pred["sequence"]) | |
| final_string = '\n'.join(k) | |
| return final_string | |
| gradio_ui = gr.Interface( | |
| fn=mask_fill, | |
| title="Predicting masked words in legal text", | |
| description="Enter a a sentence to predict the masked word", | |
| inputs=[ | |
| gr.inputs.Textbox(lines=3), | |
| ], | |
| outputs=[ | |
| gr.outputs.Textbox(label="Answer"), | |
| ], | |
| examples=[ | |
| ["The applicant submitted that her husband was subjected to treatment amounting to [MASK] whilst in the custody of police."], | |
| ], | |
| enable_queue=True, | |
| allow_screenshot=False, | |
| allow_flagging=False, | |
| ) | |
| gradio_ui.launch(debug=True) |