Instructions to use karths/binary_classification_train_service with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_service with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_service")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_service") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_service") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc69b0672f7b7036315f240998efcff18d7a9aaaec8019c88a226aa5a06bfd57
- Size of remote file:
- 4.66 kB
- SHA256:
- 11a910665f03a5670d07d42e1c885d102e5a538067baed6a273eeba3fedf173a
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