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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5638e31199d0d3ef421d01639b35a9562d9c0125bfcc7b02babf698a3f2cccb7
- Size of remote file:
- 438 MB
- SHA256:
- 6143ceda9118dd57e0bb0ce20f44e4870dec87fc068a3d25b679dc6e41bcb58d
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