Instructions to use karths/binary_classification_train_process with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_process with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_process")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_process") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_process", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 603 Bytes
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"precision": {
"ci_lower": 0.8326827725362738,
"ci_upper": 1.0477642376124137
},
"recall": {
"ci_lower": 0.8411500621375467,
"ci_upper": 1.0490333945731065
},
"f1": {
"ci_lower": 0.8369055842180666,
"ci_upper": 1.0483892193745041
},
"auc": {
"ci_lower": 0.9130252436330024,
"ci_upper": 1.034811719506867
},
"acc": {
"ci_lower": 0.8381344996595363,
"ci_upper": 1.0480917725472927
},
"mcc": {
"ci_lower": 0.6762956857025461,
"ci_upper": 1.0961816631618833
}
} |