Sentence Similarity
Transformers
PyTorch
TensorFlow
JAX
Safetensors
bert
feature-extraction
sentence_embedding
multilingual
google
text-embeddings-inference
Instructions to use setu4993/LaBSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use setu4993/LaBSE with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("setu4993/LaBSE") model = AutoModel.from_pretrained("setu4993/LaBSE") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db805ff5bedae176fd48417e425a5c12c608782e99505dd5b75989913ae47f41
- Size of remote file:
- 13.6 MB
- SHA256:
- 5aab105881afc3a73d5c8445cdc5c0302b1c3efdecd71a1a34fa0cf4e5b7bf43
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