This module includes tutorials and demos showing how to use BGE and Sentence Transformers, as well as other embedding related topics.
## [Similarity](./2_Similarity)
In this part, we show popular similarity functions and techniques about searching.
## [Indexing](./3_Indexing)
Although not included in the quick start, indexing is a very important part in practical cases. This module shows how to use popular libraries like Faiss and Milvus to do indexing.
## [Evaluation](./4_Evaluation)
In this module, we'll show the full pipeline of evaluating an embedding model, as well as popular benchmarks like MTEB and C-MTEB.
To balance accuracy and efficiency tradeoff, many retrieval system use a more efficient retriever to quickly narrow down the candidates. Then use more accurate models do reranking for the final results.