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README.md
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## Installation
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Using this model is slightly different from using typical dense embedding models. The model relies on `faiss`, for efficient indexing, and `torch`, for NN operations. JaColBERT is built upon bert-base-japanese-v3, so you also need to install the required dictionary and tokenizers:
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To use JaColBERT, you will need to install the main ColBERT and those dependencies library:
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## Installation
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**ColBERT pypy installation is temporarily broken! Please use the instructions on the [official github repo (install from Source)](https://github.com/stanford-futuredata/ColBERT) in the meantime. Sorry for the inconvenience!**
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Using this model is slightly different from using typical dense embedding models. The model relies on `faiss`, for efficient indexing, and `torch`, for NN operations. JaColBERT is built upon bert-base-japanese-v3, so you also need to install the required dictionary and tokenizers:
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To use JaColBERT, you will need to install the main ColBERT and those dependencies library:
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