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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "precision": { | |
| "ci_lower": 0.9427538899775278, | |
| "ci_upper": 1.0157979689981325 | |
| }, | |
| "recall": { | |
| "ci_lower": 0.9311403519160062, | |
| "ci_upper": 1.0159510359063146 | |
| }, | |
| "f1": { | |
| "ci_lower": 0.937012988606302, | |
| "ci_upper": 1.0157731672284585 | |
| }, | |
| "auc": { | |
| "ci_lower": 0.9827126698030874, | |
| "ci_upper": 1.0065623417223573 | |
| }, | |
| "acc": { | |
| "ci_lower": 0.9391277392497919, | |
| "ci_upper": 1.0152293902893832 | |
| }, | |
| "mcc": { | |
| "ci_lower": 0.8781878417242713, | |
| "ci_upper": 1.03049136864253 | |
| } | |
| } |