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:
- ad5ac92875b789c892026b887a17d295b3f5d646db250e2c2c60a3a6e25b69fb
- Size of remote file:
- 62.5 MB
- SHA256:
- 81652c0b575263b005ba81d0355e42ff4fbf7ef158834b98b26ca4b47c4eebbc
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