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import gradio as gr | |
from transformers import pipeline | |
pipe = pipeline("token-classification", model="cogniveon/nlpcw_bert-base-uncased-abbr", grouped_entities=True) | |
def predict(input) -> list[tuple[str, str | float | None]] | dict | None: | |
output = pipe(input) | |
return {"text": input, "entities": output} | |
demo = gr.Interface( | |
predict, | |
gr.Textbox( | |
label="Input", | |
lines=3, | |
), | |
gr.HighlightedText( | |
label="Output", | |
combine_adjacent=True, | |
show_legend=True | |
), | |
examples=[ | |
["We developed a variant of gene set enrichment analysis (GSEA) to determine whether a genetic pathway shows evidence for age regulation [23]."], | |
], | |
allow_flagging="manual", | |
flagging_options=["Correct", "Incorrect", "Ambiguous"] | |
flagging_callback=gr.CSVLogger() | |
).launch() |