Update README.md

README.md

@@ -78,11 +78,15 @@ Also note that the order of the documents is important, the first document is th
 ### Training
 
 ```python
+from sentence_transformers.cross_encoder import CrossEncoder
 from sentence_transformers.cross_encoder.evaluation import CEBinaryClassificationEvaluator
-from sentence_transformers import SentenceTransformer, InputExample, losses
+from sentence_transformers import InputExample
 
 num_epochs = 5
 model_save_path = "./model_dump"
+model_name = 'cross-encoder/nli-deberta-v3-base' # base model, use 'vectara/hallucination_evaluation_model' if you want to further fine-tune ours
+
+model = CrossEncoder(model_name, num_labels=1, automodel_args={'ignore_mismatched_sizes':True})
 
 # Load some training examples as such, using a pandas dataframe with source and summary columns:
 train_examples, test_examples = [], []