Instructions to use karths/binary_classification_train_reli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_reli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_reli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_reli") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_reli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download classification_report.json from karths/binary_classification_train_reli: direct link, hf CLI and curl.
- Browser
- Download file 516 Bytes
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https://huggingface.co/karths/binary_classification_train_reli/resolve/main/classification_report.json
- Command line
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hf download hf://karths/binary_classification_train_reli/classification_report.json
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curl -L -o classification_report.json https://huggingface.co/karths/binary_classification_train_reli/resolve/main/classification_report.json
516 Bytes
| {"0": {"precision": 0.979933110367893, "recall": 0.9898648648648649, "f1-score": 0.984873949579832, "support": 296}, "1": {"precision": 0.9885496183206107, "recall": 0.9773584905660377, "f1-score": 0.98292220113852, "support": 265}, "accuracy": 0.983957219251337, "macro avg": {"precision": 0.9842413643442518, "recall": 0.9836116777154513, "f1-score": 0.983898075359176, "support": 561}, "weighted avg": {"precision": 0.9840032968339717, "recall": 0.983957219251337, "f1-score": 0.9839520006726169, "support": 561}} |