Instructions to use facebook/regnet-y-080 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-y-080 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-y-080") 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("facebook/regnet-y-080") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-y-080") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e922df103e81c8e7ca26b96e0bce5ec7f8a38df579ca86d78df998c2af327d3d
- Size of remote file:
- 157 MB
- SHA256:
- 1a464a6eb9649935591399a0b5d1002411e8db7d0c6cf69b43099fa5fc379367
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