Instructions to use karths/binary_classification_train_build with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_build with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_build")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_build") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_build") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58e1e0d93f8cffb8eb9752e43e9c3de5b36528e55c1a45ee7af7fca1c5ff5838
- Size of remote file:
- 158 MB
- SHA256:
- 733dfa5955db9e10d260c78dfecbfb7fafc9b6a8d37eeefdf724910a8cb5f224
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