Instructions to use karths/binary_classification_train_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_main with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_main")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_main") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_main") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf50ce8b9e8ed27c1e1f854d33135f308c979e68b4f1fea442cea210063c5498
- Size of remote file:
- 4.66 kB
- SHA256:
- 43f7152cd968a9a8a252cd2b58acfd041ea56045021eafab057121ae9c56fc25
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