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:
# pip install -U transformers accelerate # 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 tf_model.h5 from setu4993/smaller-LaBSE: direct link, hf CLI and curl.
- Browser
- Download file 877 MB
-
https://huggingface.co/setu4993/smaller-LaBSE/resolve/main/tf_model.h5
- Command line
-
hf download hf://setu4993/smaller-LaBSE/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/setu4993/smaller-LaBSE/resolve/main/tf_model.h5
877 MB
- Xet hash:
- 52485ab4726c313d7d6a656ae702ea72a5e01a82d67fdf9f23ec2e96c3f3e870
- Size of remote file:
- 877 MB
- SHA256:
- 356cd054af00f8c1165bbab2eb8440e927fc5a0a352dc34f9fd9ae50fd2fdd81
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