Instructions to use karths/binary_classification_train_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_test") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 380aa89ae29c36b0c5625a44b78bbd6ead68cbf1fa4030f9c3dea2b4bb6c2a59
- Size of remote file:
- 273 MB
- SHA256:
- 97d07c0ff956c76895ced383b19eb327dda22bc4abfbf9caaa801c6604a0ffb8
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