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import gradio as gr | |
from transformers import pipeline | |
from span_marker import SpanMarkerModel | |
def function(messages): | |
# Download from the 🤗 Hub | |
model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-bert-base-acronyms") | |
# Run inference | |
# text = st.text_area('enter some text:') | |
if text: | |
out = model.predict(messages) | |
return st.json(out) | |
demo = gr.ChatInterface(fn=function, type="messages", examples=["hello", "hola", "merhaba"], title="Abbreviation-Detector") |