Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use intfloat/e5-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-base-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/e5-base-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
📋 Documentation Enhancement Suggestion
#17 opened 3 months ago
by
CroviaTrust
Adding `safetensors` variant of this model
#6 opened almost 3 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#3 opened almost 3 years ago
by
SFconvertbot
Thanks, requesting for details on instructions
1
#2 opened almost 3 years ago
by
gsaivinay
Compared with the "e5-base" model, what is the main update in this "e5-base-v2" version?
6
#1 opened almost 3 years ago
by
Zihao