Image Classification
Transformers
Tibetan
dinov3
tibetan
script-classification
paleography
fine-tuned
document-analysis
Eval Results (legacy)
Instructions to use openpecha/tibetan-script-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openpecha/tibetan-script-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="openpecha/tibetan-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("openpecha/tibetan-script-classifier", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61c0fcf0cfe3265e3a13b76d53baed25bce7ed2e9516d14a6a57787ada9a1616
- Size of remote file:
- 86.7 MB
- SHA256:
- 3aac9a9de02a2c21fcd88e5788c1a8389ccea84332381b75e168f784cabb3531
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.