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:
- 700f84511e7df6672dedcff096c3a3d0634b47b667bde6e39c48aaeb86c9c025
- Size of remote file:
- 929 kB
- SHA256:
- 6aefcb4a0fffe7a83aecbf4c8c0bfdb62d49a4c7e4ce87d60f5d96c2a4d2dc67
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