Instructions to use karths/binary_classification_train_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_main with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_main")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_main") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_main") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 113aec8f23120958979e48e72251f4565aba9af55cd1b8763d2e9f6db950a5e7
- Size of remote file:
- 30.6 MB
- SHA256:
- a9e47e794a2419fdf73b1d61aa8aae96ef6dfcb5db6f114379d2615e801727f0
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