Instructions to use TransWiC/bert-large-P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/bert-large-P with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/bert-large-P")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/bert-large-P") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/bert-large-P", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28912f2a3bfd8250dad0c33ac3cfe358d7dad348fb018466d66de6ddd4815eb6
- Size of remote file:
- 2.81 kB
- SHA256:
- 28823c3c77f4a50d0e993c24862c6823d96d5a3a8faa57f57ba6e93a25d5dda0
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