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:
- facb45dd0271f2b499f5a35a161efc3a37783b908f50c9e9ba2291a1405a7fc7
- Size of remote file:
- 1.33 GB
- SHA256:
- 20b4b83f33eb4e5b5acfd87821ba5bdbada162aa89747bedab5dc8d716fa56da
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