Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use intfloat/e5-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-large-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/e5-large-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
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Add exported onnx model 'model_O4.onnx' (#18)
Verified signature- Add exported onnx model 'model_O4.onnx' (73d388092727e42365a8a9d2a86c2a300eee65a7) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>226d082 -
Add exported onnx model 'model_qint8_avx512_vnni.onnx' (#17)
Verified signature- Add exported onnx model 'model_qint8_avx512_vnni.onnx' (72a59667edb00a2b704a7a90b276d3842dd9c654) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>febed3b -
Add exported onnx model 'model.onnx' (#16)
Verified signature- Add exported onnx model 'model.onnx' (c302f35639fbd080ba133050443276610c0b8902) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>ef82eb1