Sentence Similarity
sentence-transformers
PyTorch
Safetensors
English
bert
Sentence Transformers
text-embeddings-inference
Instructions to use intfloat/e5-large-unsupervised with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-large-unsupervised with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/e5-large-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:
- a2a2b438a5a4f5b3289d70231e86c728b268df535745313770bf9458de574a72
- Size of remote file:
- 1.34 GB
- SHA256:
- bd820d565824eb2c9de67976054ccd2d627968af8eb40b25676068a97ea39dab
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