Instructions to use karths/binary_classification_train_architecture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karths/binary_classification_train_architecture with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="karths/binary_classification_train_architecture")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("karths/binary_classification_train_architecture") model = AutoModelForSequenceClassification.from_pretrained("karths/binary_classification_train_architecture", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download metrics_std.json from karths/binary_classification_train_architecture: direct link, hf CLI and curl.
- Browser
- Download file 201 Bytes
-
https://huggingface.co/karths/binary_classification_train_architecture/resolve/main/metrics_std.json
- Command line
-
hf download hf://karths/binary_classification_train_architecture/metrics_std.json
-
curl -L -o metrics_std.json https://huggingface.co/karths/binary_classification_train_architecture/resolve/main/metrics_std.json
201 Bytes
| { | |
| "precision": 0.0745426930525177, | |
| "recall": 0.0905715537198832, | |
| "f1": 0.08262805195228776, | |
| "auc": 0.043212808010137035, | |
| "acc": 0.07728076347680288, | |
| "mcc": 0.15492129516911088 | |
| } |