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:
- 603715efed5a3bc6e19a5621150b8effbfde6765eecea8079570f68ab1cff920
- Size of remote file:
- 328 MB
- SHA256:
- b8488d3812cc2775f9fa8917117f100dfb69714e6a94cbb7a1eebc4b92e9e252
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