Instructions to use BDRC/8-class-tibetan-page-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BDRC/8-class-tibetan-page-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="BDRC/8-class-tibetan-page-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("BDRC/8-class-tibetan-page-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download split_stats.json from BDRC/8-class-tibetan-page-classifier: direct link, hf CLI and curl.
- Browser
- Download file 1.63 kB
-
https://huggingface.co/BDRC/8-class-tibetan-page-classifier/resolve/main/split_stats.json
- Command line
-
hf download hf://BDRC/8-class-tibetan-page-classifier/split_stats.json
-
curl -L -o split_stats.json https://huggingface.co/BDRC/8-class-tibetan-page-classifier/resolve/main/split_stats.json
1.63 kB
| { | |
| "source": "parquet", | |
| "classes": [ | |
| "danyig_pedri", | |
| "druma", | |
| "gyuyig_tsugdri", | |
| "multiscript", | |
| "non_tibetan", | |
| "uchen", | |
| "blank", | |
| "nonplaintext" | |
| ], | |
| "num_classes": 8, | |
| "image_counts_per_class": { | |
| "train": { | |
| "danyig_pedri": 480, | |
| "druma": 480, | |
| "gyuyig_tsugdri": 480, | |
| "multiscript": 480, | |
| "non_tibetan": 480, | |
| "uchen": 480, | |
| "blank": 480, | |
| "nonplaintext": 279 | |
| }, | |
| "val": { | |
| "danyig_pedri": 60, | |
| "druma": 60, | |
| "gyuyig_tsugdri": 60, | |
| "multiscript": 60, | |
| "non_tibetan": 60, | |
| "uchen": 60, | |
| "blank": 60, | |
| "nonplaintext": 63 | |
| }, | |
| "test": { | |
| "danyig_pedri": 60, | |
| "druma": 60, | |
| "gyuyig_tsugdri": 60, | |
| "multiscript": 60, | |
| "non_tibetan": 60, | |
| "uchen": 60, | |
| "blank": 60, | |
| "nonplaintext": 59 | |
| } | |
| }, | |
| "images_per_split": { | |
| "train": 3639, | |
| "val": 483, | |
| "test": 479 | |
| }, | |
| "images_total": 4601, | |
| "image_counts_total_per_class": { | |
| "danyig_pedri": 600, | |
| "druma": 600, | |
| "gyuyig_tsugdri": 600, | |
| "multiscript": 600, | |
| "non_tibetan": 600, | |
| "uchen": 600, | |
| "blank": 600, | |
| "nonplaintext": 401 | |
| }, | |
| "work_counts": { | |
| "train": 1881, | |
| "val": 242, | |
| "test": 413 | |
| }, | |
| "label_column": "script", | |
| "shard_files": { | |
| "train": [ | |
| "train/train-00000-of-00003.parquet", | |
| "train/train-00001-of-00003.parquet", | |
| "train/train-00002-of-00003.parquet" | |
| ], | |
| "val": [ | |
| "val/val-00000-of-00001.parquet" | |
| ], | |
| "test": [ | |
| "test/test-00000-of-00001.parquet" | |
| ] | |
| }, | |
| "parquet_hub_layout": "split_dirs" | |
| } | |