Instructions to use karths/binary_classification_train_documentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_documentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_documentation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_documentation") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_documentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 602 Bytes
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"precision": {
"ci_lower": 0.8951583031009241,
"ci_upper": 1.004710913747162
},
"recall": {
"ci_lower": 0.9023015181345099,
"ci_upper": 1.0068283950859735
},
"f1": {
"ci_lower": 0.8987228019749145,
"ci_upper": 1.0057626957098553
},
"auc": {
"ci_lower": 0.9601944289706985,
"ci_upper": 1.008107467261151
},
"acc": {
"ci_lower": 0.8984343763030347,
"ci_upper": 1.0058135285203569
},
"mcc": {
"ci_lower": 0.7968938775887061,
"ci_upper": 1.0116288954111354
}
} |