Instructions to use facebook/regnet-y-320-seer-in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-y-320-seer-in1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-y-320-seer-in1k") 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-320-seer-in1k") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-y-320-seer-in1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2193aac21f0eb9e7dad0f5ed230d2f2d6e7d6c62fa75b866a26960589beca984
- Size of remote file:
- 581 MB
- SHA256:
- aaf68c3832716b4e9f7e23bd5ccc85f59f130c7de2d25e5ef109ccc9d1a6e0f6
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