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
File size: 705 Bytes
e50372c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | {
"source": "hf",
"classes": [
"Gyuyig",
"Tsugdri"
],
"num_classes": 2,
"image_counts_per_class": {
"train": {
"Gyuyig": 171,
"Tsugdri": 171
},
"val": {
"Gyuyig": 30,
"Tsugdri": 30
},
"test": {}
},
"images_per_split": {
"train": 342,
"val": 60,
"test": 0
},
"images_total": 402,
"image_counts_total_per_class": {
"Gyuyig": 201,
"Tsugdri": 201
},
"balanced_parquet_dir": "None",
"balanced_dataset_repo": "BDRC/gyuyig-tsugdri-binary-balanced-script-classification-dataset",
"task": "gyuyig_tsugdri_binary_classification",
"benchmark_dataset_repo": null,
"benchmark_per_parent": 60,
"test_size": 120
}
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