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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8c0ad112eeafa4f0f89086c403a37ef7a1074c7ffd00c660c2eb93f9d4ecabd
- Size of remote file:
- 2.88 kB
- SHA256:
- 74b00bd5f1e20b2d928a5d360c6137943f8112062facf8656704558a1b87d728
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