Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
bert
mteb
Sentence Transformers
Eval Results (legacy)
Eval Results
text-embeddings-inference
Instructions to use Karmukilan/multilingual-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Karmukilan/multilingual-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Karmukilan/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:
- 5dfa8fba0fdfabe58c38ee782c5a4b61ead80f8e393c786a1856b3bb0ac07f60
- Size of remote file:
- 235 MB
- SHA256:
- 4654c156f3e4171abc9c716cdb771bf9116455d15ac1aab364aeeede0e3205b0
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