Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
JAX
ONNX
Safetensors
bert
feature-extraction
Eval Results
text-embeddings-inference
Instructions to use sentence-transformers/LaBSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/LaBSE with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/LaBSE") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecbdb4d3a3d851c35de2543591c18866e763ff10b25ec0e7cd660ef2801d2102
- Size of remote file:
- 1.88 GB
- SHA256:
- 77d8e1f2dbab6eb5d3c261ce9d3dbf1e3c69e02938c95f934f94f42c22dfa31f
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