Instructions to use pvl/labse_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pvl/labse_bert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("pvl/labse_bert") model = AutoModelForPreTraining.from_pretrained("pvl/labse_bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95e9f00866b26d74e5f590d2c60fa672a5e82163c1b3f58eb269359a35da2654
- Size of remote file:
- 1.89 GB
- SHA256:
- 27b3f0e602d1cfb5aeb4600c51536bf6f42cac12d6bd1a26fb150364b4869fdb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.