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:
- 5684f70b50fe6da5bb7dbf8c5f4f18b872dc03266a486a5fecae70bf9082cc83
- Size of remote file:
- 328 MB
- SHA256:
- bdd8bbb61f6591f252d1384166b0813c8f87415d880dbaa83375504f6e7af2e3
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