Sentence Similarity
sentence-transformers
PyTorch
Safetensors
English
bert
Sentence Transformers
text-embeddings-inference
Instructions to use intfloat/e5-base-unsupervised with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-base-unsupervised with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/e5-base-unsupervised") 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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add sentence similarity pipeline tag
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (9f5eaac85bfdcb72c2329cae3a88cecd77b8522d) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>79233ae
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add sentence-transformers support
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Update README.md
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Update README.md
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Update README.md
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upload models
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initial commit
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