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
Commit History
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Add exported onnx model 'model_O4.onnx' (#13)
Verified signature- Add exported onnx model 'model_O4.onnx' (4a4cddf9cf6d77a61cc1c73f824ec2127773db85) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>ccc66d3 -
Add exported onnx model 'model_qint8_avx512_vnni.onnx' (#12)
Verified signature- Add exported onnx model 'model_qint8_avx512_vnni.onnx' (095f0e876da34e2059887fa44e42d52e7909bfe7) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>6a0d452
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Adding ONNX file of this model (#4)
- Adding ONNX file of this model (919cfbe11fbf4f1b9bb321007c46c14feaf84227)ffdcc22