Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use intfloat/e5-small-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-small-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/e5-small-v2") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
-
Add exported onnx model 'model_O4.onnx' (#13)
Verified signature- Add exported onnx model 'model_O4.onnx' (58b0ed6eec5d660a4b6ded70afe590a8b8cffcaa) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>d908e34 -
Add exported onnx model 'model_qint8_avx512_vnni.onnx' (#12)
Verified signature- Add exported onnx model 'model_qint8_avx512_vnni.onnx' (c4130d3ff51a698d9f08dd4d1a957731cc0916ba) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>f17a0f7