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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() |