| from transformers import pipeline | |
| import gradio as gr | |
| # List of NER models | |
| models = ["dslim/bert-base-NER", "dslim/bert-base-NER-uncased", "dslim/bert-large-NER"] | |
| def ner(text, model_choice): | |
| ner_pipeline = pipeline("ner", model=model_choice) | |
| output = ner_pipeline(text) | |
| return {"text": text, "entities": output} | |
| examples = [ | |
| "Does Chicago have any stores and does Joe live here?", | |
| ] | |
| demo = gr.Interface( | |
| fn=ner, | |
| inputs=[ | |
| gr.Textbox(placeholder="Enter sentence here..."), | |
| gr.Dropdown(choices=models, label="Choose NER Model"), | |
| ], | |
| outputs=gr.HighlightedText(), | |
| examples=examples, | |
| ) | |
| demo.launch() | |