Update app.py

app.py

@@ -17,7 +17,8 @@ clf = pipeline(
     task="zero-shot-classification",
     model=model,
     tokenizer=tokenizer,
-    device=-1
+    device=-1,
+    framework="pt",
 )
 
 def run_zero_shot(text, labels, hypothesis_template, multi_label, top_k):
@@ -27,6 +28,7 @@ def run_zero_shot(text, labels, hypothesis_template, multi_label, top_k):
 
     if not text:
         return {"error": "Enter some text."}
+
     candidate_labels = [x.strip() for x in labels.split(",") if x.strip()]
     if not candidate_labels:
         return {"error": "Enter at least 1 label (comma-separated)."}
@@ -36,7 +38,7 @@ def run_zero_shot(text, labels, hypothesis_template, multi_label, top_k):
             sequences=text,
             candidate_labels=candidate_labels,
             hypothesis_template=hypothesis_template,
-            multi_label=bool(multi_label)
+            multi_label=bool(multi_label),
         )
 
     pairs = list(zip(out["labels"], out["scores"]))
@@ -46,7 +48,7 @@ def run_zero_shot(text, labels, hypothesis_template, multi_label, top_k):
     return {
         "top": {"label": pairs[0][0], "confidence_pct": round(pairs[0][1] * 100, 2)},
         "all": [{"label": k, "confidence_pct": round(v * 100, 2)} for k, v in pairs],
-        "raw": out
+        "raw": out,
     }
 
 demo = gr.Interface(
@@ -60,7 +62,7 @@ demo = gr.Interface(
     ],
     outputs=gr.JSON(label="Output"),
     title="Zero-Shot Classification (DeBERTa v3 Large, MoritzLaurer)",
-    allow_flagging="never"
+    flagging_mode="never",
 )
 
 if __name__ == "__main__":