Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
bert
mteb
Sentence Transformers
Eval Results (legacy)
Eval Results
text-embeddings-inference
Instructions to use intfloat/multilingual-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/multilingual-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/multilingual-e5-small") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
Add evaluation results for model intfloat/multilingual-e5-small revision fd1525a9fd15316a2d503bf26ab031a61d056e98 (#22)
614241f | - dataset: | |
| id: mteb/BRIGHT | |
| task_id: BrightStackoverflowRetrieval_default_standard | |
| revision: c26703e6600d97c579ee2985f16cf307db13ed85 | |
| value: 6.857 | |
| date: '2026-03-31' | |
| notes: Obtained using MTEB v2.10.12 | |
| source: | |
| url: https://github.com/embeddings-benchmark/mteb/ | |
| name: Obtained using MTEB v2.10.12 | |
| user: mteb | |
| - dataset: | |
| id: mteb/BRIGHT | |
| task_id: BrightStackoverflowRetrieval | |
| revision: c26703e6600d97c579ee2985f16cf307db13ed85 | |
| value: 6.857 | |
| date: '2026-03-31' | |
| notes: Obtained using MTEB v2.10.12 | |
| source: | |
| url: https://github.com/embeddings-benchmark/mteb/ | |
| name: Obtained using MTEB v2.10.12 | |
| user: mteb | |