added confidence

generic_nel.py

@@ -122,12 +122,10 @@ class NelPipeline(Pipeline):
         )
         # Process the scores for each token
 
-        # print(scores)
-        # print(type(scores), len(scores), type(list(scores)))
-        scores = torch.cat(scores, dim=0)
-        #
-        # # scores_tensor = scores.clone().detach()
-        probabilities = torch.exp(scores)
+        transition_scores = self.model.compute_transition_scores(
+            outputs.sequences, outputs.scores, normalize_logits=True
+        )
+
         # percentages = (probabilities * 100.0).cpu().numpy().tolist()
 
         # # Process each score (logits for the generated tokens)