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
Commit History
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adding st config
Michael Feil35b5119
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Update README.md
b281623
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Fix SummEval scores (https://github.com/embeddings-benchmark/mteb/pull/99) (#2)
- Fix SummEval scores (https://github.com/embeddings-benchmark/mteb/pull/990) (e18e2eb5aff0261fdfa5d6e9a0192a5ce4348835) Co-authored-by: Niklas Muennighoff <Muennighoff@users.noreply.huggingface.co>c31dd12
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Update README.md
a421e2c
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Update README.md
e755844
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update README.md
9195f2b
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upload model
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initial commit
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