Instructions to use karths/binary_classification_train_defect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_defect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_defect")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_defect") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_defect") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac2096fadb1d198ea1e5b02a8da5c81733a1b7c7e2646d149f60d734834230ff
- Size of remote file:
- 929 kB
- SHA256:
- 348ac9240e6d203f1f8df7bcd9c14602028f3997b8713255f13d36e92f98e8e2
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