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Hi,
Thanks for releasing the gold passages and the queries.
It seems that the prebuilt learned dense index for the wiki corpus for both English and French is not available on HuggingFace (for the …
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Hello,
I am interested in exploring the possibility of adding the [ColBERT model](https://github.com/stanford-futuredata/ColBERT) to the current examples available for BERT. ColBERT's approach to den…
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Here is the issue, I will keep a record of all my findings as I work on the task of refining all aspects of the retrieval system on different datasets using dense retrievals.
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### Feature request
[BGE-M3](https://huggingface.co/BAAI/bge-m3), which is distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity.
+ Multi-Functionality:…
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My dataset is creating an index of 10GB using Qdrant in langchain. I am creating both dense and sparse vectors. I am having issues with slow performance both creating the vectorstore ( took almost 6 d…
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Getting
`ApiError: status_code: 401, body: {'detail': 'Not authenticated'}`
despite all variables are set propperly.
Exploring file_retrieve_workflow.ipynb and constantly getting this error. Any…
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A starting point could be using pyserini' dense model for Msmarco first.
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### Feature request
I want to run the `https://huggingface.co/prithivida/Splade_PP_en_v1` using infinity. While it loads the model, but the output isn't the sparse representation. It being a sparse e…
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Congratulations on your impressive work! In order to reproduce your results more conveniently, could you please share your candidate documents on MS MARCO (Dense Retrieval)?
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