Create app.py

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("ua-l/topics-classifier")
+model = AutoModelForSequenceClassification.from_pretrained(
+    "ua-l/topics-classifier"
+)
+
+topic_classifier = pipeline(
+    task="text-classification", model=model, tokenizer=tokenizer, device="cpu", top_k=5
+)
+
+def predict(question):
+    predictions = topic_classifier(question)
+
+    topics = []
+    for prediction in predictions[0]:
+        label = prediction["label"]
+        probability = round(prediction["score"] * 100, 2)
+
+        topics.append(
+            {
+                "label": label,
+                "probability": probability,
+            }
+        )
+
+    return str(topics)
+
+demo = gr.Interface(fn=predict, inputs="text", outputs="text")
+demo.launch()