Instructions to use pierric/ny-cr-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pierric/ny-cr-fr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pierric/ny-cr-fr") 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("pierric/ny-cr-fr") model = AutoModelForImageClassification.from_pretrained("pierric/ny-cr-fr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfacc713fe4187bf624df736f7ac7b816f953e1f0a60bf07baabb20e9161f854
- Size of remote file:
- 343 MB
- SHA256:
- 7bbb33cdad356d83b11331d4d99d666bf13199d5b6df695ced8acad53e9fb319
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