Instructions to use karths/binary_classification_train_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_test") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 249d8f134c856f375a1de85248668ba3a05b10a54808fc9f708decc453db6671
- Size of remote file:
- 657 MB
- SHA256:
- 05ee76986e2272e709be4dc76b27e4ac6ed9fbaa9322a1d92890995e014ad9ac
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