Instructions to use karths/binary_classification_train_automation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_automation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_automation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_automation") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_automation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c64a00d6c73a96d06fca1459c608f8492844b82de9a177796695e16de29c5f0
- Size of remote file:
- 929 kB
- SHA256:
- 8d7c500564a382e6eb01e452d09c56a8feb695886538a82715613588f4714cf6
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