Instructions to use TransWiC/bert-large-E with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/bert-large-E with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/bert-large-E")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/bert-large-E") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/bert-large-E", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57eaedc939356cffa3ab15db97b072531902fb4f767ac3bf4f98e3bfbf4508a6
- Size of remote file:
- 2.66 GB
- SHA256:
- 508d354a926c7b6f11630ee7291837a4e35d6c262de5b70dc25ffca308400cdd
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