intfloat/multilingual-e5-large
feature-extraction model by intfloat
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Model card & documentation
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Multilingual E5 Text Embeddings: A Technical Report. Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei, arXiv 2024 This model has 24 layers and the embedding size is 1024. Below is an example to encode queries and passages from the MS-MARCO passage ranking dataset. This model is initialized from xlm-roberta-large and continually trained on a mixture of multilingual datasets. It supports 100 languages from xlm-roberta, but low-resource languages may see performance degradation. Initialization: xlm-roberta-large First stage: contrastive pre-training with weak supervision Second stage: supervised fine-tuning For all labeled datasets, we only use its training set for fine-tuning. For other training details, please refer to our paper at https://arxiv.org/pdf/2402.05672. Check out unilm/e5 to reproduce evaluation results on the BEIR and MTEB benchmark. Below is an example for usage with sentencetransformers. Package requirements pip install sentencetransformers=2.2.2 Contributors: michaelfeil 1. Do I need to add the prefix "query: " and…
Read the full model card ↗ · Preview checked 2026-10-28T18:57:01.081Z
Inside the original model card — Document outline
- Multilingual-E5-large
- Usage
- Supported Languages
- Training Details
- Benchmark Results on Mr. TyDi
- MTEB Benchmark Evaluation
- Support for Sentence Transformers
- FAQ
- Citation
- Limitations
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Documentation belongs to its respective authors. Reported project/model license: mit. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
intfloat/multilingual-e5-large is a feature-extraction model repository published by intfloat 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
- feature-extraction
- Library
- sentence-transformers
- Recent downloads (30 days)
- 6,724,393
- Cumulative likes
- 1,282
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 559,890,946
- Architecture
- XLMRobertaModel
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2023-06-30T07:38:19.000Z
- Last modified
- 2026-04-02T02:16:59.000Z
Compatibility and lineage
Reported languages: multilingual, af, am, ar, as, az, be, bg, bn, br, bs, ca, cs, cy, da, de, el, en, eo, es, et, eu, fa, fi, fr, fy, ga, gd, gl, gu, ha, he, hi, hr, hu, hy, id, is, it, ja
Base-model lineage was not included.
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 2026-11-01T06:54:29.511Z. Daily imports are snapshots, not real-time monitoring.
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