Instructions to use karths/binary_classification_train_secu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_secu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_secu")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_secu") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_secu") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99735dd95d1a0e227d12d393e9abbfc2b6bea88b7ec6cad954966af25104c165
- Size of remote file:
- 18 MB
- SHA256:
- 7bd1ee4018c549461ff593acefdea2a07c6835ff6b714d78fb6c94207a6f638b
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