Update README.md

README.md

@@ -10,4 +10,4 @@ resizing to 256x256 and then converting to grayscale and then applying the Fouri
 4. Feed into model input
 
 The model will then transform the input transform into a 128-length embedding vector. These vectors are separable and can be used in classification models.
-The model doesn't enforce a specific classification model, prototypical networks, XGBoost, and other classifiers can be used to classify.
+The model doesn't enforce a specific classification model, prototypical networks, XGBoost, and other classifiers can be used to classify. For more detailed instructions refer to [Kaggle](https://www.kaggle.com/models/nhrade/cgi-embedding-detection-module).