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:
- 33ec2a11bf39f7ff43f81225b88e9f1758403119221aa7e6173bbef2aa5419fc
- Size of remote file:
- 1.33 GB
- SHA256:
- 889b9de985ea55414cd11a2c4442f19317d40346757a6e7c915b83d1e1002604
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