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 metrics_std.json from karths/binary_classification_train_perf: direct link, hf CLI and curl.
- Browser
- Download file 203 Bytes
-
https://huggingface.co/karths/binary_classification_train_perf/resolve/main/metrics_std.json
- Command line
-
hf download hf://karths/binary_classification_train_perf/metrics_std.json
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curl -L -o metrics_std.json https://huggingface.co/karths/binary_classification_train_perf/resolve/main/metrics_std.json
203 Bytes
| { | |
| "precision": 0.03720266873587592, | |
| "recall": 0.034270783411463834, | |
| "f1": 0.03572970487644412, | |
| "auc": 0.01488391732575064, | |
| "acc": 0.03544020140627279, | |
| "mcc": 0.07086600340705013 | |
| } |