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README.md
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> There is currently no JaColBERTv2 technical report. For an overall idea, you can refer to the JaColBERTv1 [arXiv Report](https://arxiv.org/abs/2312.16144)
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---
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inference: false
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datasets:
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- bclavie/mmarco-japanese-hard-negatives
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- unicamp-dl/mmarco
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language:
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- ja
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pipeline_tag: sentence-similarity
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tags:
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- ColBERT
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base_model:
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- cl-tohoku/bert-base-japanese-v3
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- bclavie/JaColBERT
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license: mit
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library_name: RAGatouille
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---
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First version of JaColBERTv2. Weights might be updated in the next few days.
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Current early checkpoint is fully functional and outperforms multilingual-e5-large, BGE-M3 and JaColBERT in early results, but full evaluation TBD.# Intro
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> There is currently no JaColBERTv2 technical report. For an overall idea, you can refer to the JaColBERTv1 [arXiv Report](https://arxiv.org/abs/2312.16144)
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