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:
- 6ac34a035fb2881eb4977c26ff91391d3e27e5760f7ff509bbe79e6c7ad7e37f
- Size of remote file:
- 28.1 MB
- SHA256:
- 1d0f3242bc9c8a4a37ad72a1bd80d63d5fef8c9cc207f47cf1de437b51d6e1e4
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