Instructions to use facebook/regnet-x-008 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-x-008 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-x-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-x-008") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-x-008", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45c77474174e8db20c67f3a2b8ed9455c3c36921b916b450c8970ff88292b554
- Size of remote file:
- 29.3 MB
- SHA256:
- 70f56b1607d22458b2361408c5132f61187f57fe37716b96df3729cd4f27bb3f
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