Instructions to use TransWiC/bert-large-CLS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/bert-large-CLS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/bert-large-CLS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/bert-large-CLS") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/bert-large-CLS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fffe919dfcb0d527e34043e36b0b5ce4f030d7465f186f91efee46448c014a04
- Size of remote file:
- 1.33 GB
- SHA256:
- 57472954742cdc50bc6a0b818a8d96f72f8b922f06f8fdfe3fd724d1e8c6375e
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