Instructions to use karths/binary_classification_train_reli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_reli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_reli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_reli") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_reli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 109bcf2ebd4cb906226557b8711bd55346b77bd2f888a4b37ed60a63e136e3ca
- Size of remote file:
- 15.9 MB
- SHA256:
- 1e98eb0830b288764b3664aaeb8d04acb8b5e716c98141f78b5c404f921d56a9
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