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  # opensearch-neural-sparse-encoding-multilingual-v1
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  ## Select the model
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- The model should be selected considering search relevance, model inference and retrieval efficiency(FLOPS). We benchmark models' performance on a subset of MIRACL benchmark (we exclude th since the uncased backbone can not encode it).
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- ** We recommend to use it with max_ratio pruning. **
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  | Model | Inference-free for Retrieval | Model Parameters | AVG NDCG@10 | AVG FLOPS |
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  |-------|------------------------------|------------------|-------------|-----------|
 
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  # opensearch-neural-sparse-encoding-multilingual-v1
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  ## Select the model
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+ The model should be selected considering search relevance, model inference and retrieval efficiency(FLOPS). We benchmark models' performance on **MIRACL** benchmark (we exclude th since the uncased backbone can not encode it).
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+ **We recommend to use it with max_ratio pruning.**
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  | Model | Inference-free for Retrieval | Model Parameters | AVG NDCG@10 | AVG FLOPS |
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  |-------|------------------------------|------------------|-------------|-----------|