Instructions to use facebook/regnet-x-080 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-x-080 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-x-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-x-080") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-x-080", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b32ba1955e3e434913395eb1e84e479883ae63fe80ec020b64ec4f6db4d743b
- Size of remote file:
- 159 MB
- SHA256:
- 24a9e85c5188f858f37cffb30c01af4d0599b392e158860f4adc2dd94dc58fd7
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