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_russian_mteb_scores
#9
by Samoed - opened
I've added mteb results for Russian models while testing the merging of existing code to integrate the README with new results. The diff looks janky because some keys were shuffled, and at some point, mteb changed its export style. If you decide to close this PR, that's fine, as I will add these scores to the mteb results repository.
Samoed changed pull request status to open
Thanks for the contribution, I'll merge this pull request.
intfloat changed pull request status to merged