Add application file

app.py

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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()

requirements.txt

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+transformers
+torch