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* docs: update README.md and index.md with example link for Retrieval Embedding Generation

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README.md
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FastEmbed is an easy to use -- lightweight, fast, Python library built for retrieval embedding generation.
The default embedding supports "query" and "passage" prefixes for the input text. The default model is Flag Embedding, which is top of the [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard.
The default embedding supports "query" and "passage" prefixes for the input text. The default model is Flag Embedding, which is top of the [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard. Here is an example for [Retrieval Embedding Generation](https://qdrant.github.io/fastembed/examples/Retrieval%20with%20FastEmbed/)
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FastEmbed is an easy to use -- lightweight, fast, Python library built for retrieval embedding generation. The default embedding supports "query" and "passage" prefixes for the input text.
The default model is Flag Embedding, which is top of the [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard.
The default model is Flag Embedding, which is top of the [MTEB](https://huggingface.co/spaces/mteb/leaderboard) leaderboard. Here is an example for [Retrieval Embedding Generation](https://qdrant.github.io/fastembed/examples/Retrieval%20with%20FastEmbed/)
## 🚀 Installation
To install the FastEmbed library, pip works: