Instructions to use karths/binary_classification_train_comp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_comp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_comp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_comp") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_comp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f97aa87428f66073d53f84937a8fae5a37d9bd89e6bc4918b145e68e79caf5b4
- Size of remote file:
- 135 MB
- SHA256:
- 41d8e1e3865f3312ed20c352a03a598802f2f71c7016e8ef21522680dbdb45b9
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