Sentence Similarity
sentence-transformers
Safetensors
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use maiyad/multilingual-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use maiyad/multilingual-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("maiyad/multilingual-e5-small") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a6de4985f106f58b2c51a0190a2f4cea67a63ae83cb71206a0c78546091a111
- Size of remote file:
- 17.1 MB
- SHA256:
- 6710678b12670bc442b99edc952c4d996ae309a7020c1fa0096dd245c2faf790
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