Update README.md

README.md

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-license: mit
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+---
+license: mit
+---
+
+This repo contains the code needed to run AIR-Bench using llamaindex.
+
+In this repo, I implement a custom retriever that uses `text-embedding-ada-002` as the dense embedding model, bm25 for sparse embeddings, and the `QueryFusionRetriever()` to combine results from these two, as well as generating extra queries for retrieval.
+
+## Usage
+
+`pip install llama-index llama-index-retrievers-bm25`
+
+`python ./run_airbench.py`
+
+## Customization
+
+Feel free to use this as a template to evaluate other llama-index retrieval pipelines! You just need to customize the setup in `create_retriever_fn()` with the setup that you want to test against.