Instructions to use facebook/regnet-x-002 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-x-002 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-x-002") 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-002") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-x-002", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00078096b4f6b3bf807aafa7ad74aa83e2a03907100af5e9e2a85131299fadba
- Size of remote file:
- 11.1 MB
- SHA256:
- c0b289b0582eabb3a5b8f92832f34af0059268e2785770bd407c38ba17c21965
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