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:
# pip install -U transformers accelerate # 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
Commit History
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Adding `safetensors` variant of this model
This is an automated PR create with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. Feel free to ignore this PR.8d279db
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Re-export model with TF 2.9
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Re-export from latest version of `transformers`
Track `tokenizers.json` with lfs`cc32fa2
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Update model card
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Update model card for v2
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Update model to v2
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Automatic correction of README.md metadata for keys. Contact website@huggingface.co for any question
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Re-add model card
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Re-add incorrectly removed models, tokenizer
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upload flax model
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allow flax
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Add model card
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Add Google's license
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Export tf model from pt model
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Export converted tokenizer
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Add exported pytorch model
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initial commit
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