Instructions to use BDRC/gyuyig-tsugdri-binary-script-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BDRC/gyuyig-tsugdri-binary-script-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="BDRC/gyuyig-tsugdri-binary-script-classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BDRC/gyuyig-tsugdri-binary-script-classifier", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "split": "test", | |
| "labels": [ | |
| "Gyuyig", | |
| "Tsugdri" | |
| ], | |
| "matrix": [ | |
| [ | |
| 58, | |
| 2 | |
| ], | |
| [ | |
| 16, | |
| 44 | |
| ] | |
| ], | |
| "test_metrics": { | |
| "loss": 0.40474860469500223, | |
| "accuracy": 0.85, | |
| "macro_f1": 0.847930160518164, | |
| "weighted_f1": 0.847930160518164, | |
| "auc_roc": 0.9297222222222223 | |
| }, | |
| "val_metrics": { | |
| "loss": 0.3914561231931051, | |
| "accuracy": 0.9166666666666666, | |
| "macro_f1": 0.9164578111946533, | |
| "weighted_f1": 0.9164578111946533, | |
| "auc_roc": 0.9311111111111111 | |
| }, | |
| "preprocess": { | |
| "train": "center_crop", | |
| "val": "center_crop", | |
| "test": "center_crop", | |
| "size": 224 | |
| }, | |
| "train_dataset": "BDRC/gyuyig-tsugdri-binary-balanced-script-classification-dataset", | |
| "benchmark_per_parent": 60, | |
| "experiment": "dinov3_gyuyig_tsugdri_binary", | |
| "repo_id": "BDRC/gyuyig-tsugdri-binary-script-classifier" | |
| } | |