# Information Retrieval Reranking

Ms Marco TinyBERT L6
Apache-2.0
A cross-encoder model trained on the MS Marco passage ranking task, suitable for query-passage relevance scoring in information retrieval scenarios.
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cross-encoder
6,963
1
Ms Marco TinyBERT L4
Apache-2.0
An information retrieval model optimized based on the TinyBERT architecture, specifically trained for the MS Marco passage ranking task
Text Embedding English
M
cross-encoder
380
1
Ms Marco TinyBERT L2
Apache-2.0
A lightweight cross-encoder trained on the MS Marco passage ranking task for query-passage relevance scoring in information retrieval
Text Embedding English
M
cross-encoder
71.76k
18
Ms Marco Electra Base
Apache-2.0
A cross-encoder trained on the ELECTRA-base architecture, specifically optimized for the MS Marco passage ranking task, used for query-passage relevance scoring in information retrieval.
Text Embedding Transformers English
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cross-encoder
118.93k
5
Ms Marco TinyBERT L2 V2
Apache-2.0
A lightweight cross-encoder trained on the MS Marco passage ranking task for query-passage relevance scoring in information retrieval
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cross-encoder
247.59k
25
Ms Marco MiniLM L4 V2
Apache-2.0
A cross-encoder model trained on the MS Marco passage ranking task for scoring query-passage relevance in information retrieval
Text Embedding English
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cross-encoder
234.18k
10
Ms Marco MiniLM L6 V2
Apache-2.0
A cross-encoder model trained on the MS Marco passage ranking task for query-passage relevance scoring in information retrieval
Text Embedding English
M
cross-encoder
2.5M
86
Ms Marco MiniLM L12 V2
Apache-2.0
A cross-encoder model trained on the MS Marco passage ranking task for relevance ranking in information retrieval.
Text Embedding English
M
cross-encoder
469.35k
71
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