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:
- b64023df596eb28f0dc16da8442b3ce067efb3c3e56669624c332910f2c49761
- Size of remote file:
- 1.88 GB
- SHA256:
- e07832909d014a85584fd6fd4d1192ef3752cf46a4dfa8825dfbae1193d6c425
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