Instructions to use karths/binary_classification_train_usab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_usab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_usab")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_usab") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_usab") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5f37fcb3a0f4ccd2ddea1a328b25a98e3596e8fa8375c1a231ee45a7e6e7ca9
- Size of remote file:
- 328 MB
- SHA256:
- beadc08a56f100fde4c91910066cb811227f3ed59602afeddc2f31ca16e578af
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