Image Classification
Transformers
Tibetan
tibetan
uchen
ume
script-classification
dinov3
fine-tuned
Eval Results (legacy)
Instructions to use openpecha/uchen-ume-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openpecha/uchen-ume-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="openpecha/uchen-ume-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("openpecha/uchen-ume-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 705 Bytes
7d64bbf 6839bbd 7d64bbf 6839bbd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"checkpoint": "without_preprocess/final_model.pt",
"n_images": 60,
"preprocess": "none",
"metrics": {
"loss": 0.3956117908159892,
"accuracy": 0.85,
"macro_f1": 0.847930160518164,
"weighted_f1": 0.847930160518164,
"auc_roc": 0.97
},
"report": " precision recall f1-score support\n\n uchen 0.78 0.97 0.87 30\n ume 0.96 0.73 0.83 30\n\n accuracy 0.85 60\n macro avg 0.87 0.85 0.85 60\nweighted avg 0.87 0.85 0.85 60\n",
"confusion_matrix": [
[
29,
1
],
[
8,
22
]
]
}
|