Instructions to use karths/binary_classification_train_usab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_usab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_usab")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_usab") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_usab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download classification_report.json from karths/binary_classification_train_usab: direct link, hf CLI and curl.
- Browser
- Download file 527 Bytes
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https://huggingface.co/karths/binary_classification_train_usab/resolve/bf73d26480d615feafcb400aeacdb31d09bb2888/classification_report.json
- Command line
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hf download hf://karths/binary_classification_train_usab@bf73d26480d615feafcb400aeacdb31d09bb2888/classification_report.json
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curl -L -o classification_report.json https://huggingface.co/karths/binary_classification_train_usab/resolve/bf73d26480d615feafcb400aeacdb31d09bb2888/classification_report.json
527 Bytes
| {"0": {"precision": 0.9952986725663717, "recall": 0.9952986725663717, "f1-score": 0.9952986725663717, "support": 3616}, "1": {"precision": 0.9949329359165425, "recall": 0.9949329359165425, "f1-score": 0.9949329359165425, "support": 3355}, "accuracy": 0.9951226509826424, "macro avg": {"precision": 0.9951158042414572, "recall": 0.9951158042414572, "f1-score": 0.9951158042414572, "support": 6971}, "weighted avg": {"precision": 0.9951226509826424, "recall": 0.9951226509826424, "f1-score": 0.9951226509826424, "support": 6971}} |