Update README.md

upload v2 regression, fixed version

README.md

@@ -21,6 +21,7 @@ There are three BERT models, each fine-tuned on a dataset of 70K Python 3 soluti
 - `bert_lc100_hp25`: This model classifies code based on the 25th percentile as its threshold. It is designed for identifying lower quartile code solutions in terms of quality or performance.
 - `bert_lc100_hp50`: Operating with a median-based approach, this model uses the 50th percentile as its classification threshold. It is suitable for general assessments, providing a balanced view of code quality.
 - `bert_lc100_regression`: Unlike the others, this is a regression model. It provides a nuanced prediction of the overall code quality score, offering a more detailed evaluation compared to the binary classification approach.
+- `bert_lc100_regression_v2`: similar to `bert_lc100_regression` model, the correctness score is calculated using more restricted rule `==` instead of similarity.
 
 ## Model Usage
 **Installation**