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:
- 55f8162e98885b4ca275956e42f9ed7be924c3a4e9934097502f51c06a9d5a92
- Size of remote file:
- 22.5 MB
- SHA256:
- a9df1deca86bedc499abb972ea6ede37c1c40a82bc1ae9b2eab94e230390cecc
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