Instructions to use karths/binary_classification_train_perf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_perf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_perf")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_perf") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_perf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download classification_report.json from karths/binary_classification_train_perf: direct link, hf CLI and curl.
- Browser
- Download file 529 Bytes
-
https://huggingface.co/karths/binary_classification_train_perf/resolve/main/classification_report.json
- Command line
-
hf download hf://karths/binary_classification_train_perf/classification_report.json
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curl -L -o classification_report.json https://huggingface.co/karths/binary_classification_train_perf/resolve/main/classification_report.json
529 Bytes
| {"0": {"precision": 0.9974519047012358, "recall": 0.9949167619773795, "f1-score": 0.9961827204478941, "support": 7869}, "1": {"precision": 0.9947923447467778, "recall": 0.9973893747552539, "f1-score": 0.9960891669925694, "support": 7661}, "accuracy": 0.9961365099806826, "macro avg": {"precision": 0.9961221247240069, "recall": 0.9961530683663167, "f1-score": 0.9961359437202317, "support": 15530}, "weighted avg": {"precision": 0.9961399350417959, "recall": 0.9961365099806826, "f1-score": 0.9961365702211561, "support": 15530}} |