Update README.md

README.md

@@ -49,6 +49,8 @@ I got the idea from this [LLM classifier](https://github.com/lamini-ai/llm-class
 The model utilizes Few-Shot Learning techniques through SetFit, requiring only 8 examples per class. It can be trained in less than 1 minute on an RTX 3060 graphics card. 
 This method provides an efficient solution for developing lightweight models suitable for real-world applications.
 
+The source code can be found in my repo [mrzaizai2k/LLM-with-RAG](https://github.com/mrzaizai2k/LLM-with-RAG)
+
 This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
 
 The model has been trained using an efficient few-shot learning technique that involves: