answerdotai
answerdotai/JaColBERTv2.5
No description available.
Model Documentation
Model weights for the final JaColBERTv2.5 checkpoint, using an entirely overhauled training recipe and trained on just 40% of the data of JaColBERTv2.
This model largely outperforms all previous approaches, including JaColBERTV2 multilingual models such as BGE-M3, on all datasets.
This page will be updated with the full details and the model report in the next few days.
This model largely outperforms all previous approaches, including JaColBERTV2 multilingual models such as BGE-M3, on all datasets.
This page will be updated with the full details and the model report in the next few days.
@misc{clavié2024jacolbertv25optimisingmultivectorretrievers,
title={JaColBERTv2.5: Optimising Multi-Vector Retrievers to Create State-of-the-Art Japanese Retrievers with Constrained Resources},
author={Benjamin Clavié},
year={2024},
eprint={2407.20750},
archivePrefix={arXiv},
primaryClass={cs.IR},
url={https://arxiv.org/abs/2407.20750},
}
Files & Weights
| Filename | Size | Action |
|---|---|---|
| model.safetensors | 0.41 GB |