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:
- f143556768446c7b3646f8ff4e1122cac30c96ef8f4aa50712b7e92bcd58d7a5
- Size of remote file:
- 1.33 GB
- SHA256:
- 006d94ff85766cdc3107a575efe91da8a161a1ba72ede5821896e58c634280ba
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