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:
- 6dd043859b85d4b5f3bde4a381c4cff7e070aedea46c3cc827ea3c2b6ed6cb43
- Size of remote file:
- 3.52 kB
- SHA256:
- 3876cf49c93d3a583a3b2bcad675de8a40591289c60497810ff3ac4f56a8ce3a
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