attempted bugfix

app.py

@@ -19,10 +19,16 @@ if __name__ == "__main__":
 
     # Define your color-coding labels; if prob > x, then label = y; Sorted in descending probability order!
     probs_to_label = [
+        (0.9, "p >= 90%"),
         (0.8, "p >= 80%"),
+        (0.7, "p >= 70%"),
+        (0.6, "p >= 60%"),
         (0.5, "p >= 50%"),
+        (0.4, "p >= 40%"),
+        (0.3, "p >= 30%"),
         (0.2, "p >= 20%"),
-        (0.0, "p >= 0%")
+        (0.1, "p >= 10%"),
+        (0.0, "p >= 00%")
     ]
 
     label_to_color = {
@@ -42,7 +48,7 @@ if __name__ == "__main__":
         )
         # Important: don't forget to set `normalize_logits=True` to obtain normalized probabilities (i.e. sum(p) = 1)
         transition_scores = model.compute_transition_scores(outputs.sequences, outputs.scores, normalize_logits=True)
-        transition_proba = np.exp(transition_scores)
+        transition_proba = np.exp(transition_scores[0])
         # We only have scores for the generated tokens, so pop out the prompt tokens
         input_length = 1 if model.config.is_encoder_decoder else inputs.input_ids.shape[1]
         generated_ids = outputs.sequences[:, input_length:]