Feature Extraction
Transformers
bert
ctranslate2
int8
float16 - bert - sentence_embedding - multilingual - google - sentence-similarity
text-embeddings-inference
Instructions to use michaelfeil/ct2fast-LaBSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelfeil/ct2fast-LaBSE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="michaelfeil/ct2fast-LaBSE")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("michaelfeil/ct2fast-LaBSE") model = AutoModel.from_pretrained("michaelfeil/ct2fast-LaBSE") - Notebooks
- Google Colab
- Kaggle
Commit History
Upload setu4993/LaBSE ctranslate fp16 weights 55f08ae
Upload setu4993/LaBSE ctranslate fp16 weights a95ceb9
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initial commit d7e28b9
Michael commited on