cross-encoder/ms-marco-MiniLM-L4-v2
text-ranking model by cross-encoder
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Model card & documentation
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This model was trained on the MS Marco Passage Ranking task. The model can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch). Then sort the passages in a decreasing order. See SBERT.net Retrieve & Re-rank for more details. The training code is available here: SBERT.net Training MS Marco The usage is easy when you have…
Read the full model card ↗ · Preview checked 2026-10-28T22:30:51.160Z
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Model overview
cross-encoder/ms-marco-MiniLM-L4-v2 is a text-ranking model repository published by cross-encoder on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-ranking
- Library
- sentence-transformers
- Recent downloads (30 days)
- 3,864,224
- Cumulative likes
- 52
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 19,165,185
- Architecture
- BertForSequenceClassification
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2022-03-02T23:29:05.000Z
- Last modified
- 2025-08-29T14:36:22.000Z
Compatibility and lineage
Reported languages: en
Reported base models: cross-encoder/ms-marco-MiniLM-L12-v2
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-31T06:49:12.816Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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