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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03e35e11b3745265c031998c3df746830076b107432fcc3613e1cdc30dd952a5
- Size of remote file:
- 2.39 GB
- SHA256:
- 42f3822dc5b625bc22e98ac2b742d91c5f10e5b7724351ba33be0b905706e94c
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