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 tokenizer.json from sentence-transformers/LaBSE: direct link, hf CLI and curl.
- Browser
- Download file 9.62 MB
-
https://huggingface.co/sentence-transformers/LaBSE/resolve/main/tokenizer.json
- Command line
-
hf download hf://sentence-transformers/LaBSE/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/sentence-transformers/LaBSE/resolve/main/tokenizer.json
9.62 MB
File too large to display, you can check the raw version instead.