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:
- 16de677c612cd1b35d11f56e369abbff83c6545b42a5ceab271d2d219cb6df87
- Size of remote file:
- 929 kB
- SHA256:
- 92481253160d5cbba0a7b60408539dfa646826cc2a2ed4884b995ce9da213c48
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