Feature Extraction
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
xlm-roberta
mteb
Sentence Transformers
sentence-similarity
Eval Results (legacy)
Eval Results
text-embeddings-inference
Instructions to use vllm-project/multilingual-e5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use vllm-project/multilingual-e5-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vllm-project/multilingual-e5-large") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Add provenance note for vLLM CI copy
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README.md
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license: mit
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## Multilingual-E5-large
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[Multilingual E5 Text Embeddings: A Technical Report](https://arxiv.org/pdf/2402.05672).
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license: mit
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<!-- vllm-ci-copy -->
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> [!NOTE]
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> This is a copy of [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) at commit `3d7cfbd`, made on 2026-10-30. vLLM CI uses this checkpoint and the original is on a personal account, so we keep a copy here to reduce supply-chain risk.
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## Multilingual-E5-large
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[Multilingual E5 Text Embeddings: A Technical Report](https://arxiv.org/pdf/2402.05672).
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