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import gradio as gr |
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from transformers import pipeline |
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get_completion = pipeline("ner", model="dslim/bert-base-NER") |
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def ner(input): |
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output = get_completion(input) |
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return {"text": input, "entities": output} |
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demo = gr.Interface(fn=ner, |
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inputs=[gr.Textbox(label="Text to find entities", lines=2)], |
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outputs=[gr.HighlightedText(label="Text with entities")], |
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title="NER with dslim/bert-base-NER", |
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description="Find entities using the `dslim/bert-base-NER` model under the hood!", |
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allow_flagging="never", |
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examples=["My name is Andrew and I live in California", "My name is Poli and work at HuggingFace"]) |
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demo.launch() |
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