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
Download 2_Dense/pytorch_model.bin from sentence-transformers/LaBSE: direct link, hf CLI and curl.
- Browser
- Download file 2.36 MB
-
https://huggingface.co/sentence-transformers/LaBSE/resolve/main/2_Dense/pytorch_model.bin
- Command line
-
hf download hf://sentence-transformers/LaBSE/2_Dense/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sentence-transformers/LaBSE/resolve/main/2_Dense/pytorch_model.bin
2.36 MB
- Xet hash:
- e805ee8f5cc71ba80f8f8dde08e325885cc2c04f88b90bf20285ee7a1dff1d90
- Size of remote file:
- 2.36 MB
- SHA256:
- 06fb85120e40adf0ab188c4f0cc7684f702cb2023532947d1b85f325b0a3645c
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