Instructions to use facebook/convnextv2-base-1k-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnextv2-base-1k-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnextv2-base-1k-224") 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/convnextv2-base-1k-224") model = AutoModelForImageClassification.from_pretrained("facebook/convnextv2-base-1k-224") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8e032f2dfc27b0e362aabb989bbb1c79d1b2fe7693a99d379f69d73c27c6bf6
- Size of remote file:
- 355 MB
- SHA256:
- 1e561cccf1c8c3815f5b3f1067e71c56c48393368f9a19973220b8dcccd2eb1e
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