Instructions to use TransWiC/bert-large-ET with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/bert-large-ET with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/bert-large-ET")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/bert-large-ET") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/bert-large-ET", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19f0643a3da98e0ce1aac6f983e07fbb98545069b0136dd59e2f386557befbce
- Size of remote file:
- 2.81 kB
- SHA256:
- 2d42cb174732c195f77260b13667ac9154d0c06cd7541d4bae16a603b003db32
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