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:
- 2f8d5dd8dd8fa851f95aa815eeb5dffa7ac849215dcca806f4e635442ca44ebd
- Size of remote file:
- 331 MB
- SHA256:
- b0c1a7857da57115bd390adbb2fdf818114e12552997834630f39a2ef1531105
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