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:
- 0609d70734407bcc9ff344243a6807d3b87b5155e2c943db610203cce260aaee
- Size of remote file:
- 580 MB
- SHA256:
- 52f67bd0e9dcb89dc9803e313f55a34a6fa2737785c3933f64b5cf21ea93d719
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