add confidence

generic_nel.py

@@ -96,20 +96,17 @@ class NelPipeline(Pipeline):
             max_new_tokens=30,
         )
         print(outputs)
-        token_ids, scores = outputs.sequences, outputs.sequences_scores
-        wikipedia_titles = self.tokenizer.batch_decode(
-            token_ids, skip_special_tokens=True
-        )
-        scores_tensor = scores.clone().detach()
-        probabilities = torch.exp(scores_tensor)
-        percentages = (probabilities * 100.0).cpu().numpy().tolist()
+        # token_ids, scores = outputs.sequences, outputs.sequences_scores
+        # scores_tensor = scores.clone().detach()
+        # probabilities = torch.exp(scores_tensor)
+        # percentages = (probabilities * 100.0).cpu().numpy().tolist()
 
         wikipedia_predictions = self.tokenizer.batch_decode(
             outputs, skip_special_tokens=True
         )
         # print(f"Decoded: {wikipedia_predictons}")np.round(percentages[i], 2)
 
-        return wikipedia_predictions, percentages
+        return wikipedia_predictions, [0, 0, 0, 0, 0]
 
     def _forward(self, inputs):
         return inputs