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
- Xet hash:
- 7b7c692f53ac1b90fc9e64e0395985b2b4ca6562e4c75e5ed0c40710c3452072
- Size of remote file:
- 86.7 MB
- SHA256:
- 9cce9a6920cff9cd5fc7add0a40b81969f36383fc1919fcb4c0adb1b0f2047b1
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