Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use AbdullahMoQH/multilingual-e5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AbdullahMoQH/multilingual-e5-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AbdullahMoQH/multilingual-e5-base") 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:
- 1a682c31e6f0de549b0797cf976f17661e87e0b04d24af0e79838e4ba796a4ab
- Size of remote file:
- 1.11 GB
- SHA256:
- 4d4f1d21c425da5b1ee3598243e6bbb87e0be4a10e3f7a8deab9139dc2a65538
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