add inference func

app.py

@@ -9,6 +9,19 @@ auth_token = os.environ.get("TOKEN_FROM_SECRET")
 model = DistilBertForSequenceClassification.from_pretrained(MODEL_PATH, use_auth_token=auth_token)
 tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-uncased")
 
+clf = pipeline("text-classification", model=model.to("cpu"), tokenizer=tokenizer)
+
+
+def clf_result(text_input: str) -> str:
+
+    model_res = clf(text_input)[0]
+    label_map = {"LABEL_0": "NOT RISKY", "LABEL_1": "RISKY"}
+    label_res = label_map.get(model_res["label"])
+    score = model_res["score"]
+    res = f"Result: {label_res}\n\nScore: {score}"
+    return res
+
+
 demo = gr.Interface(
     fn=clf_result,
     title="Test High Risk Words model v2",