Update README.md

README.md

@@ -134,19 +134,17 @@ print(sentences.shape)  # E.g. a batch of 1 sentence
 
 import onnxruntime as ort
 
-sess = ort.InferenceSession(
-  "path_to_model_dot_onnx",
-  providers=['CPUExecutionProvider'],
-)
+sess = ort.InferenceSession("path_to_model_dot_onnx", providers=['CPUExecutionProvider'])
 
-outputs = [o.name for o in sess.get_outputs()]
+outputs = [o.name for o in sess.get_outputs()]  # list of labels, in the order of the outputs
 preds_onnx = sess.run(_outputs, {'logits': _label_embeddings})
-# preds_onnx is a list with 28 entries, each with a numpy array of shape (1, 2)
+# preds_onnx is a list with 28 entries, one per label,
+# each with a numpy array of shape (1, 2) given the input was a batch of 1
 
 print(outputs[0])
-# surprise
+> surprise
 print(preds_onnx[0])
-# array([[0.97136074, 0.02863926]], dtype=float32)
+> array([[0.97136074, 0.02863926]], dtype=float32)
 ```
 
 ### Commentary on the dataset