Instructions to use TransWiC/bert-large-P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/bert-large-P with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/bert-large-P")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/bert-large-P") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/bert-large-P") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eae8c0402ee0c9e051af4b27454576a8e4af06b3812cb748e21761c4153cb021
- Size of remote file:
- 627 Bytes
- SHA256:
- a93a77a513e2e8c74a0f7643b089a6503701a057afe58a9c7890e0113b7dc464
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