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import gradio as gr
from transformers import pipeline
# Define the models
model = pipeline("text-classification",
model="OpenAlex/bert-base-multilingual-cased-finetuned-openalex-topic-classification-title-abstract")
def classify_text(text, top_k):
result = model(text, top_k=top_k, truncation=True, max_length=512)
return {p["label"]: p["score"] for p in result}
with gr.Blocks() as demo:
gr.Interface(
fn=classify_text,
inputs=[gr.Textbox(lines=5, label="Text", placeholder="<TITLE> {title}\n<ABSTRACT> {abstract}",
value="<TITLE> {title}\n<ABSTRACT> {abstract}"),
gr.Number(label="top_k", value=10, precision=0)],
outputs=gr.Label(label="openalex topic predicted"),
title="OpenAlex topic classification",
description="Enter a text and see the topic classification result!",
flagging_mode="never",
api_name="classify"
)
if __name__ == "__main__":
print(gr.__version__)
demo.launch()
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