updated

README.md

@@ -169,12 +169,17 @@ SentenceTransformer(
 )
 ```
 
-## Usage
+# Fine-Tuned BGE-Small Model for Q&A
 
-### Direct Usage (Sentence Transformers)
+This is a `BAAI/bge-small-en-v1.5` model that has been fine-tuned for a specific Question & Answering task using the `MultipleNegativesRankingLoss` in the `sentence-transformers` library.
 
-First install the Sentence Transformers library:
+It has been trained on a private dataset of 100,000+ question-answer pairs. Its primary purpose is to be the retriever model in a Retrieval-Augmented Generation (RAG) system. It excels at mapping questions to the passages that contain their answers.
 
+## How to Use (Practical Inference Example)
+
+The primary use case is to find the most relevant passage for a given query.
+
+```python
 from sentence_transformers import SentenceTransformer, util
 
 # Load the fine-tuned model from the Hub
@@ -201,11 +206,12 @@ passage_embeddings = model.encode(passages)
 similarities = util.cos_sim(query_embedding, passage_embeddings)
 
 # 4. Print the results
-print(f"Query: {query.replace(instruction, '')}\n")
+print(f"Query: {query.replace(instruction, '')}\\n")
 for i, passage in enumerate(passages):
     print(f"Similarity: {similarities[0][i]:.4f} | Passage: {passage}")
 ```
 
+
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 ### Direct Usage (Transformers)