| import gradio as gr |
| from tner import TransformersNER |
| from spacy import displacy |
|
|
| model = TransformersNER("tner/roberta-large-ontonotes5") |
| |
|
|
| examples = [ |
| "Jacob Collier is a Grammy awarded artist from England.", |
| "When Sebastian Thrun started working on self-driving cars at Google in 2007 , few people outside of the company took him seriously.", |
| "But Google is starting from behind. The company made a late push into hardware, and Apple’s Siri, available on iPhones, and Amazon’s Alexa software, which runs on its Echo and Dot devices, have clear leads in consumer adoption." |
| ] |
|
|
|
|
| def predict(text): |
| output = model.predict([text]) |
| tokens = output['input'][0] |
|
|
| def retain_char_position(p): |
| if p == 0: |
| return 0 |
| return len(' '.join(tokens[:p])) + 1 |
|
|
| doc = { |
| "text": text, |
| "ents": [{ |
| "start": retain_char_position(entity['position'][0]), |
| "end": retain_char_position(entity['position'][-1]) + len(entity['entity'][-1]), |
| "label": entity['type'] |
| } for entity in output['entity_prediction'][0]], |
| "title": None |
| } |
|
|
| html = displacy.render(doc, style="ent", page=True, manual=True, minify=True) |
| html = ( |
| "<div style='max-width:100%; max-height:360px; overflow:auto'>" |
| + html |
| + "</div>" |
| ) |
| |
| return html |
|
|
|
|
| demo = gr.Interface( |
| fn=predict, |
| inputs=gr.inputs.Textbox( |
| lines=5, |
| placeholder="Input sentence...", |
| ), |
| outputs="html", |
| examples=examples |
| ) |
| demo.launch() |
|
|
