Instructions to use karths/binary_classification_train_requirement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_requirement with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_requirement")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_requirement") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_requirement") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cabf504b85f233e7827827c6f9051d41114408347c69dff12b061ea505e96a64
- Size of remote file:
- 32 MB
- SHA256:
- 6c88a9c9a4333860e88c3d35f029aec742bd73dc3d8a53b0619af1a8992b9962
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