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-[Embeddings](#embeddings)
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-[Types of vectors](#types-of-vectors)
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-[Dense vectors](#dense-vectors)
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-[Size of input and Chunking](#size-of-input-and-chunking)
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-[Positional chunking](#positional-chunking)
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-[Semantic chunking](#semantic-chunking)
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-[Matryoshka embeddings](#matryoshka-embeddings)
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-[Sparse vectors](#sparse-vectors)
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-[SPLADE](#splade)
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##### Dense Vectors
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###### Size of input and Chunking
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-[Chunking Strategies for LLM Applications](https://www.pinecone.io/learn/chunking-strategies/)
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-[Evaluating the Ideal Chunk Size for a RAG System using LlamaIndex](https://blog.llamaindex.ai/evaluating-the-ideal-chunk-size-for-a-rag-system-using-llamaindex-6207e5d3fec5)
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-[How to Chunk Text Data — A Comparative Analysis](https://towardsdatascience.com/how-to-chunk-text-data-a-comparative-analysis-3858c4a0997a)
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####### Positional chunking
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####### Semantic chunking
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###### Matryoshka embeddings
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*[Matryoshka embeddings: faster OpenAI vector search using Adaptive Retrieval](https://supabase.com/blog/matryoshka-embeddings)
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