Instructions to use karths/binary_classification_train_build with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_build with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_build")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_build") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_build") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25110b842c9012e289cbabf3dae352db54c7329839eebc367d6d163658d4349a
- Size of remote file:
- 328 MB
- SHA256:
- 99d90de7783c499123fe65e335d2cde00dd1a30a1100aef423f0e83cfe1db8a6
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