jina-colbert-v1-en
Maintainer: jinaai
76
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Jina-ColBERT
Jina-ColBERT is a variant of the ColBERT retrieval model that is based on the JinaBERT architecture. Like the original ColBERT, Jina-ColBERT uses a late interaction approach to achieve fast and accurate retrieval. The key difference is that Jina-ColBERT supports a longer context length of up to 8,192 tokens, enabled by the JinaBERT backbone which incorporates the symmetric bidirectional variant of ALiBi.
Model inputs and outputs
Inputs
- Text passages to be indexed and searched
Outputs
- Ranked lists of the most relevant passages for a given query
Capabilities
Jina-ColBERT is designed for efficient and effective passage retrieval, outperforming standard BERT-based models. Its ability to handle long documents up to 8,192 tokens makes it well-suited for tasks involving large amounts of text, such as document search and question-answering over long-form content.
What can I use it for?
Jina-ColBERT can be used to power a wide range of search and retrieval applications, including enterprise search, academic literature search, and question-answering systems. Its performance characteristics make it particularly useful in scenarios where users need to search large document collections quickly and accurately.
Things to try
One interesting aspect of Jina-ColBERT is its ability to leverage the JinaBERT architecture to support longer input sequences. Practitioners could experiment with using Jina-ColBERT to search through long-form content like books, legal documents, or research papers, and compare its performance to other retrieval models.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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