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Jina AI launches open-source 8k text embedding

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Re: Jina AI launches open-source 8k text embedding

#4
Impressive work.

I wonder what would be the best way to use 8k embeddings. It’s a lot of information to keep in a vector, so things like “precision” of the embedding space and its ability to distinguish very similar large documents will be key.

Maybe it can be useful for coarse similarity matching, for example to detect plagiarism?

Re: Jina AI launches open-source 8k text embedding

#7
post #4

Impressive work. I wonder what would be the best way to use 8k embeddings. It’s a lot of information to keep in a vector, so things like “precision” of the embedding space and its ability to distinguish very similar large documents will be key. Maybe it can be useful for coarse similarity matching, for example to detect plagiarism?

8K is the context length. Their vector dimension size is actual much smaller, which is great for a number of use cases, though maybe not the ones you are thinking about.

Re: Jina AI launches open-source 8k text embedding

#9
Some relevant stats from the link:

8192 token input sequence length

768 embedding dimensions

0.27GB model (with 0.07GB model also available)

Tokeniser: BertTokenizer [1], 30528 token vocab [2]

Is an 8K sequence length directly comparable to text-embedding-ada-002 if the vocabulary is much smaller? I seem to remember its tokeniser has a larger vocabulary.

[1] https://huggingface.co/jinaai/jina-embeddings-v2-base-en/blo...

[2] https://huggingface.co/jinaai/jina-embeddings-v2-base-en/blo...

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