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
📋 Documentation Enhancement Suggestion
#26 opened 3 months ago
by
CroviaTrust
📋 Documentation Enhancement Suggestion
#25 opened 3 months ago
by
CroviaTrust
add AIBOM
#24 opened 11 months ago
by
RiccardoDav
How can I get large corpus dataset (over 200 Millions of records) in a tsv file format to encode with intfloat/e5-large-v2 as an embedding model ?
#15 opened about 2 years ago
by
liorf95
Comparison with multilingual-e5-large
#14 opened over 2 years ago
by
xuuxu
Single input vs Multiple inputs
1
#13 opened over 2 years ago
by
innovationTony
Possible Vector Collaps Issue
1
#10 opened almost 3 years ago
by
Banso
Changing the dimensions of the embeddings
1
#9 opened almost 3 years ago
by
Suijhin
Adding ONNX file of this model
#5 opened almost 3 years ago
by
asifanchor
Adding `safetensors` variant of this model
#4 opened almost 3 years ago
by
SFconvertbot
e5-large-v2 requirements for training in non english?
2
#3 opened almost 3 years ago
by
wilfoderek
Which embedding vector to use?
8
#2 opened almost 3 years ago
by
moooji
How can I support the max_length=2048
6
#1 opened almost 3 years ago
by
nlpdev3