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I appreciate the work you're doing with the Beir benchmark – it's very useful.
I'm developing a library that enables training models like Splade, Sparsembed, BLP, and Colbert using PyTorch. I've included Beir in the requirements to facilitate evaluations during training. However, I'm facing an issue. I want to utilize Faiss GPU with my own retriever for evaluating my models on Beir benchmarks and I don't wan't to install Faiss CPU.
I'm wondering if it's possible to create a custom extras_requires section in your setup.py that would exclude Faiss for users who don't intend to use Beir retrievers.
Hi,
I appreciate the work you're doing with the Beir benchmark – it's very useful.
I'm developing a library that enables training models like Splade, Sparsembed, BLP, and Colbert using PyTorch. I've included Beir in the requirements to facilitate evaluations during training. However, I'm facing an issue. I want to utilize Faiss GPU with my own retriever for evaluating my models on Beir benchmarks and I don't wan't to install Faiss CPU.
I'm wondering if it's possible to create a custom extras_requires section in your setup.py that would exclude Faiss for users who don't intend to use Beir retrievers.
Here is an example:
pip install "beir[no_faiss]"
I'm fine with creating a PR if you are ok with this.
Thank you,
Raphaël
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