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:
- 17b5b61b0668f24dfb8225c32a256306ada3483d985d0332e714c2ffb7a4f788
- Size of remote file:
- 328 MB
- SHA256:
- fd02bdc975460faf678d88889d59c4c26d939d75537094da9902c7b0ad705bab
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