Instructions to use karths/binary_classification_train_defect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_defect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_defect")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_defect") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_defect") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 850a272307f39d24e30e90d17b75776bfaa91bbd46a5d24071858a24485f5249
- Size of remote file:
- 331 MB
- SHA256:
- 9eadfa90895c7c89a287c5e0aa9c135f4f080717d9c7c5425477e4a1f17e1c87
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