Instructions to use ndavid/binary-question-classifier-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ndavid/binary-question-classifier-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ndavid/binary-question-classifier-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ndavid/binary-question-classifier-bert") model = AutoModelForSequenceClassification.from_pretrained("ndavid/binary-question-classifier-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0893e9325bc9eb12500a2f3e26dea6f9dc2e36bf0ab0f1827ec722750d9df282
- Size of remote file:
- 433 MB
- SHA256:
- 91adc68f3bcc85c5f0e80197ec93e7713eb8a33bc6f36f17cfbce6cf7f18be6b
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