Instructions to use facebook/convnextv2-tiny-1k-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnextv2-tiny-1k-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnextv2-tiny-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-tiny-1k-224") model = AutoModelForImageClassification.from_pretrained("facebook/convnextv2-tiny-1k-224") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3718100a2e823c16c68d96e5fd6ded0db8653827a17ea0ed3bd25766ece00fe5
- Size of remote file:
- 115 MB
- SHA256:
- 18059f267af456845431c96c43a2a82ad930dc96c2cbbb1136327a9a4e92f05d
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