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:
- 6e374345cf16cacc550018c10777991ad220ec5d654f5113e943b95dfb3071b5
- Size of remote file:
- 331 MB
- SHA256:
- ca15ab86929dd3ca03b625e142a8554531f390778bc2ed678fae182661fbf101
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