Instructions to use facebook/regnet-y-008 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-y-008 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-y-008") 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-008") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-y-008", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23ae14efc72789fc3242520c9ab2b6a7dfe2410a5f6797c0df88cb885d01530a
- Size of remote file:
- 25.3 MB
- SHA256:
- a7df156a9c86b6db6b6c3223038e7784f45bfd56df5b117736bf5be608efafee
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