Instructions to use karths/binary_classification_train_TD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_TD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_TD")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_TD") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_TD") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 409b3db04798178619f83c71e27deffd6ca0a83db83b05a60af65886dfb5fc89
- Size of remote file:
- 88 MB
- SHA256:
- ac536bfffefd15feeeb999cfc144401d6c6c7d7e971b97a47cf35b0992c72eb1
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