Instructions to use karths/binary_classification_train_documentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_documentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_documentation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_documentation") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_documentation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee0e22f5deb1c7b0b2d2a9dc08ac43f860ce03ae1f5bb21a40e1ce611bd33cda
- Size of remote file:
- 657 MB
- SHA256:
- ba64fcd226ef55d2905eaf4977b25772211e1e9a068848369730f7d0a1610f7f
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