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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 278092060f7697dc22bd92ab6e0d32c18df6bb9aea64260e6c438f1f446fbc75
- Size of remote file:
- 331 MB
- SHA256:
- 93907d5506b28b392cf76a7cb0ecec3164d8e763caec78632febd49eee1d7d3c
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