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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openpecha/tibetan-script-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download whole_page/final_model.pt from openpecha/tibetan-script-classifier: direct link, hf CLI and curl.
- Browser
- Download file 86.7 MB
-
https://huggingface.co/openpecha/tibetan-script-classifier/resolve/main/whole_page/final_model.pt
- Command line
-
hf download hf://openpecha/tibetan-script-classifier/whole_page/final_model.pt
-
curl -L -o final_model.pt https://huggingface.co/openpecha/tibetan-script-classifier/resolve/main/whole_page/final_model.pt
86.7 MB
- Xet hash:
- 1fdb7605423a3ef095ee3663f1853d2e798183ec0f2681bc4faeea1def75e85a
- Size of remote file:
- 86.7 MB
- SHA256:
- 987f2d4139415491e3323eb8a6a622365d1b336897dfb07383d35146a2afb38f
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