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README.md

@@ -103,8 +103,12 @@ class ASJCMultiLabelPipeline(TextClassificationPipeline):
     def postprocess(self, model_outputs, **kwargs):
         # Convert logits to probabilities using sigmoid
         scores = torch.sigmoid(torch.tensor(model_outputs["logits"])).tolist()
-        results = []
 
+        # Handle single-input batch: take the first element
+        if isinstance(scores[0], list):
+            scores = scores[0]
+
+        results = []
         for i, score in enumerate(scores):
             if score >= self.threshold:
                 label = self.model.config.id2label[str(i)]