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Update README.md (#8)
Browse files- Update README.md (55e5a5e8f73a773d71584222991e349f843e64ea)
Co-authored-by: Denis Sushentsev <[email protected]>
README.md
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The embedding model was trained using 512 sequence length, but extrapolates to 8k sequence length (or even longer) thanks to ALiBi.
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This makes our model useful for a range of use cases, especially when processing long documents is needed, including technical question answering and code search.
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This model has
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Additionally, we provide the following embedding models:
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- [`jina-embeddings-v2-small-en`](https://huggingface.co/jinaai/jina-embeddings-v2-small-en): 33 million parameters.
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The embedding model was trained using 512 sequence length, but extrapolates to 8k sequence length (or even longer) thanks to ALiBi.
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This makes our model useful for a range of use cases, especially when processing long documents is needed, including technical question answering and code search.
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This model has 161 million parameters, which enables fast and memory efficient inference, while delivering impressive performance.
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Additionally, we provide the following embedding models:
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- [`jina-embeddings-v2-small-en`](https://huggingface.co/jinaai/jina-embeddings-v2-small-en): 33 million parameters.
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