Instructions to use TransWiC/bert-large-BT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/bert-large-BT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/bert-large-BT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/bert-large-BT") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/bert-large-BT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46cb06e3078f5c7c47f358a5cc088c17ef7a3a5f09774e573d014edb2be48b1b
- Size of remote file:
- 2.66 GB
- SHA256:
- 41e3b9bf9c5df4ac75f4370301058ecb9d03b997ebffa95cc9783511f5a6350e
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