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:
- dd4d7f7b2384266b360dc68a375360dd4f03d3d1db470af7202fc59c0edfd3c3
- Size of remote file:
- 2.67 GB
- SHA256:
- a74fbfcbc5f22edf8a316abcc0a99d0b480ff7ca07e15080ffdc46eefbafbf1b
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