Sentence Similarity
sentence-transformers
PyTorch
Safetensors
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use intfloat/e5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/e5-base") 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
Download pytorch_model.bin from intfloat/e5-base: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/intfloat/e5-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://intfloat/e5-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/intfloat/e5-base/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 9247cff7ea8c650e55a9c4e40a6b28a4d9167dfc7dce9c56fbfaf3790a5700f9
- Size of remote file:
- 438 MB
- SHA256:
- bd623a40c8b841b7c99a464e32e6629d19935a52d123d1ebda7b26606b5de637
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