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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9410ae17219e80d72def6f7fc0b01769d1ffc8962467f561bebcf88e2beef671
- Size of remote file:
- 687 MB
- SHA256:
- a95385b925cf456a550c041f98452d06ddd840142594d4dd9ecb3fb40ce71db8
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