Trained by Jina AI . Jina ColBERT Jina ColBERT is a ColBERT style model but based on JinaBERT so it can support both 8k context length , fast and accurate retrieval . JinaBERT is a BERT architecture that supports the symmetric bidirectional variant of ALiBi to allow longer sequence length. The Jina ColBERT model is trained on MSMARCO passage ranking dataset, following a very similar training procedure with ColBERTv2. The only difference is that we use jina bert v2 base en as the backbone instead of bert base uncased . For more information about ColBERT, please refer to the ColBERTv1 and ColBERTv2 paper, and the original code. Usage Installation To use this model, you will need to install the latest version of the ColBERT repository: Indexing Searching Creating Vectors Complete working Colab Notebook is here Reranking Using ColBERT Evaluation Results TL;DR: Our Jina ColBERT achieves the competitive retrieval performance with ColBERTv2 on all benchmarks, and outperforms ColBERTv2 on datasets in where documents have longer context length. In domain benchmarks We evaluate the in domain performance on the dev subset of MSMARCO passage ranking dataset. We follow the same evaluation setti…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy