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:
- 26309b682ecf2fd02c8bf5092dd1078d361145a3f35be457f23a5bc0afe866c1
- Size of remote file:
- 928 kB
- SHA256:
- 4cbefdd2ce7b4be5236b6e3a4448227ae16f1b1d40b15784225adb098856b7a2
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