Instructions to use karths/binary_classification_train_code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_code")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_code") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_code") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd652c38f0bb790b28803850ebcad43f03d8b6f467953fae7cbae7844250ea04
- Size of remote file:
- 657 MB
- SHA256:
- df67bf6b83ac2642dbe50cbf5fb9c059aec32985697b7ada2fde6c21337cb5ed
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