Instructions to use TransWiC/bert-large-CLS-BT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/bert-large-CLS-BT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/bert-large-CLS-BT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/bert-large-CLS-BT") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/bert-large-CLS-BT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89731496e68aca086c71462fd9bd0dc16c4c0c3381f735df05c44bae02d4d4a5
- Size of remote file:
- 2.66 GB
- SHA256:
- 621259fd97774fa0b79fdc47980eb1500c263eb96295b476ded07d629cd998f8
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