Instructions to use TransWiC/bert-large-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/bert-large-B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/bert-large-B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/bert-large-B") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/bert-large-B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28dffa245f4124c8f13a49d14c4e8db10dd18229a5042f0cc74e27b44d3b79c1
- Size of remote file:
- 2.66 GB
- SHA256:
- 0316e55963849242c81fd62815b7e7996ab968066bc85697f927bc76425709dd
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