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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b4edd2a8ce9aa68fb09eb58f12e89ad339cf20aab89df19f497b2bcc5248be8
- Size of remote file:
- 1.88 GB
- SHA256:
- a2965837da030339e5e05b7fd1be813cb17b8ddaec5ed9f0a6f0ac9881019b5e
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