Update README.md

README.md

@@ -3,12 +3,11 @@ license: mit
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 # Dataset Card for NextGLab FAISS-v2.0
 
-## Dataset Summary
 The NextGLab FAISS-v2.0 dataset is a dense vector index designed for Retrieval-Augmented Generation (RAG) tasks. It is constructed by embedding text from:
 - [srsRAN Project](https://github.com/srsran/srsRAN_Project): A complete 5G RAN solution featuring an ORAN-native CU/DU.
 - O-RAN Alliance specifications
 
-### Dataset Details
+## Summary
 - **Total Documents**: 88,808
 - **Total Words**: 7,236,372
 - **Embedding Model**: [BAAI/bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5)
@@ -56,11 +55,6 @@ for doc in retrieved_docs:
     print(doc.page_content)
 ```
 
-## Use Cases
-- **O-RAN Research & Development**: Quickly retrieve relevant O-RAN specifications and srsRAN implementations.
-- **LLM-Enhanced Knowledge Retrieval**: Use as a backend for Retrieval-Augmented Generation (RAG) models focused on telecom.
-- **Telecom-Specific AI Applications**: Build smarter AI assistants for wireless communication systems.
-
 ## Citation
 A detailed paper documenting the experiments and results achieved with this FAISS vector store will be available soon. Meanwhile, if you try this model, please cite the paper mentioned below to acknowledge the foundational work that enabled it.