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29 lines
1.1 KiB
Markdown
29 lines
1.1 KiB
Markdown
# FlagEmbedding_tutorial
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If you are new to here, check out the 5 minute [quick start](./quick_start.ipynb)!
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<details>
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<summary>Tutorial roadmap</summary>
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<img src="./tutorial_map.png"/>
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</details>
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## [Embedding](./1_Embedding)
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This module includes tutorials and demos showing how to use BGE and Sentence Transformers, as well as other embedding related topics.
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## [Similarity](./2_Similarity)
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In this part, we show popular similarity functions and techniques about searching.
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## [Indexing](./3_Indexing)
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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.
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## [Evaluation](./4_Evaluation)
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In this module, we'll show the full pipeline of evaluating an embedding model, as well as popular benchmarks like MTEB and C-MTEB.
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## [Reranking](./5_Reranking/)
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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.
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