Sentence Similarity
Transformers
PyTorch
TensorFlow
JAX
Safetensors
bert
feature-extraction
sentence_embedding
multilingual
google
labse
text-embeddings-inference
Instructions to use setu4993/smaller-LaBSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use setu4993/smaller-LaBSE with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("setu4993/smaller-LaBSE") model = AutoModel.from_pretrained("setu4993/smaller-LaBSE", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from setu4993/smaller-LaBSE: direct link, hf CLI and curl.
- Browser
- Download file 877 MB
-
https://huggingface.co/setu4993/smaller-LaBSE/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://setu4993/smaller-LaBSE@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/setu4993/smaller-LaBSE/resolve/refs%2Fpr%2F1/pytorch_model.bin
877 MB
- Xet hash:
- 5a3a823e68628501711921c1ce53eb4911ac6802620b52dc4323be1c82548a1b
- Size of remote file:
- 877 MB
- SHA256:
- 86df18d5ac34c03f0da7b6e205fc6f0a8948553ec6e8f06ef6f9382bc5183ecc
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