Instructions to use karths/binary_classification_train_infrastructure with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_infrastructure with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_infrastructure")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_infrastructure") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_infrastructure") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cd5259b630de9fddef5dfdde2a470e99c3df7cca3168f7a375651ed0a33c102
- Size of remote file:
- 4.66 kB
- SHA256:
- fad545aa56e39547604a6aec89a48aa9d41070fb3f411ae2857c916de8c0bf55
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