Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use intfloat/e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/e5-small") 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
- Xet hash:
- 7a19bcf154a9e500d68c6f7a2ba416f40ddda42c14ca69faa542f90e3a1d90c0
- Size of remote file:
- 133 MB
- SHA256:
- 96ec59525cd3b8ede24f5517c89188354c46f347d60fb9566b0dd4ea9dfcda0c
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