Instructions to use tjpel/SignModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tjpel/SignModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tjpel/SignModel") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("tjpel/SignModel") model = AutoModelForImageClassification.from_pretrained("tjpel/SignModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2db5d04a1c8dad501bd7060106b7c7450d85c4f5859fd99cc33b02b6f4aa0c20
- Size of remote file:
- 343 MB
- SHA256:
- 3e5a8e47d0c82ac9fc35305d3744ce6940c50cca3a8b566d9a59408643991608
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