Sentence Similarity
sentence-transformers
PyTorch
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use embaas/sentence-transformers-multilingual-e5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use embaas/sentence-transformers-multilingual-e5-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("embaas/sentence-transformers-multilingual-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
- Xet hash:
- 81d63204a496678121b465cb8323ee875d6c0b54230f5281edd6a8607030b925
- Size of remote file:
- 1.11 GB
- SHA256:
- f061cb7641880f52895cbacab7c4ab39b0844e2e6b73794f2798de460d9fa418
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