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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd0d343b0c0dc08174118f8659a6c2c735a1e991d771614011eb8dba695968a9
- Size of remote file:
- 86.7 MB
- SHA256:
- 6753c4b49f6fa52b6d4580b926070cdea8dba7908f0e3a562f60dd42512e3148
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