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add comparison benchmark for embedding models

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Massive Text Embedding Benchmark (MTEB) Leaderboard: https://huggingface.co/spaces/mteb/leaderboard
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@ -11,6 +11,8 @@ For more information, read OpenAI's blog post announcements:
* [Introducing Text and Code Embeddings (Jan 2022)](https://openai.com/blog/introducing-text-and-code-embeddings/)
* [New and Improved Embedding Model (Dec 2022)](https://openai.com/blog/new-and-improved-embedding-model/)
For comparison with other embedding models, see [Massive Text Embedding Benchmark (MTEB) Leaderboard](https://huggingface.co/spaces/mteb/leaderboard)
## Semantic search
Embeddings can be used for search either by themselves or as a feature in a larger system.