Instructions to use NM-development/LaBSE-en-ru-ce-prototype with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NM-development/LaBSE-en-ru-ce-prototype with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("NM-development/LaBSE-en-ru-ce-prototype") model = AutoModelForPreTraining.from_pretrained("NM-development/LaBSE-en-ru-ce-prototype") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50a2edee58687b24b5876570594a07f10dd2fdfa19f441d77eb42c4fc04ab7dc
- Size of remote file:
- 567 MB
- SHA256:
- 9fd783764cadab7277b8846f6de8bcb0884caae8907a04a63b3ca3e86085156d
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