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:
- f5823feedc26e8690cbdb86c833d98476cca65016818feb26dfffa3036f5c8d7
- Size of remote file:
- 2.81 kB
- SHA256:
- 54066a722ffd82b9a802dea48820624ed53df939112ffff09bda73ebfc5a2e1c
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