Instructions to use facebook/convnextv2-nano-22k-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnextv2-nano-22k-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnextv2-nano-22k-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-nano-22k-224") model = AutoModelForImageClassification.from_pretrained("facebook/convnextv2-nano-22k-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92ce1a5097a968ce791a246122b7a7d302eba3021ce66a1f6300b03056ab625f
- Size of remote file:
- 62.7 MB
- SHA256:
- 206f60095ac32ac950b451c40002d44c0fb1bcd2ba092496e97f862e59e955e3
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