Instructions to use facebook/regnet-y-032 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-y-032 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-y-032") 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-032") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-y-032", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66fdba6bdd0d2878a67c5ebb5a3e210e495fadb33943c77a3cce970b6b1f9746
- Size of remote file:
- 78.5 MB
- SHA256:
- 43aabfabb501a5857bee50d781d895b4d7524059e532c1444f4576b08eddc288
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