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:
- 047b7dda1a1485566992cda4420566665ee7f2746a7c2f0ad0b3670b68fab29b
- Size of remote file:
- 3.24 GB
- SHA256:
- 8a5340dde3e3f20944d5a65939df6a598e43a0fc378b0c8f9ac76d93f275d796
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