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:
- 9046720a0bee2851c5c58dc2dc7124b270fcee7b24943be98eefd47310c74460
- Size of remote file:
- 109 MB
- SHA256:
- bd22c53e406404b7e72a272ea0d724b06215bffc3af8be60dbde04a6dc17c9e3
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