Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
xlm-roberta
mteb
Sentence Transformers
Eval Results (legacy)
Eval Results
text-embeddings-inference
Instructions to use intfloat/multilingual-e5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/multilingual-e5-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/multilingual-e5-base") 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
-
Add link to new paper
Verified signaturecea84a7
-
Adding ONNX file of this model (#11)
- Adding ONNX file of this model (7d8760377f73aadb2f2a4e31fff2e48d2cbe68bf) Co-authored-by: Romain <romaindeveaud@users.noreply.huggingface.co>167cf6a
-
Update README.md
b1a0e29
-
add sentence similarity tag
061a1bb
-
Update README.md
1292863
-
track tokenizer.json with lfs
1881441
-
Adding `safetensors` variant of this model (#6)
- Adding `safetensors` variant of this model (5c31b33181f6c6bfbbce758a5900f9407bbcff42) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>a1c23e4
-
Update README.md
716cad0 -
sentence transformers (#5)
- sbert (73faffbff62768f15b166b0b6866e99b993f6be4)830e3a9
-
Update README.md
f7d866c
-
upload model weights
8bbd5fa -
initial commit
ddf1713