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README.md
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data_files:
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- split: test
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path: da.jsonl
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---
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# Dataset Description
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This is the [MKQA](https://github.com/apple/ml-mkqa?tab=readme-ov-file) ***with query embeddings***, which can be used jointly with [Multilingual Embeddings for Wikipedia in 300+ Languages](https://huggingface.co/datasets/Cohere/wikipedia-2023-11-embed-multilingual-v3) for doing multilingual passage retrieval, since the vectors are calculated via the same embedder [Cohere Embed v3](https://cohere.com/blog/introducing-embed-v3).
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data_files:
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- split: test
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path: da.jsonl
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- config_name: de
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data_files:
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- split: test
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path: de.jsonl
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- config_name: en
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data_files:
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- split: test
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path: en.jsonl
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- config_name: es
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data_files:
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- split: test
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path: es.jsonl
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- config_name: fi
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data_files:
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- split: test
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path: fi.jsonl
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- config_name: fr
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data_files:
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- split: test
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path: fr.jsonl
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- config_name: he
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data_files:
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- split: test
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path: he.jsonl
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- config_name: hu
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data_files:
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- split: test
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path: hu.jsonl
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---
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# Dataset Description
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This is the [MKQA](https://github.com/apple/ml-mkqa?tab=readme-ov-file) ***with query embeddings***, which can be used jointly with [Multilingual Embeddings for Wikipedia in 300+ Languages](https://huggingface.co/datasets/Cohere/wikipedia-2023-11-embed-multilingual-v3) for doing multilingual passage retrieval, since the vectors are calculated via the same embedder [Cohere Embed v3](https://cohere.com/blog/introducing-embed-v3).
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