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:
- a64bd62c3dd896bd88a4ffac019f6aba7766553f41d3229f64ebe650f3e6bd51
- Size of remote file:
- 13.2 MB
- SHA256:
- 6939b4a1df4b574395d37dce88b09b02d14162b0790175334232151393fdce39
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