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:
- d259446f1eba282d4e27e4f92c7ae2cc8cd190dae0e181fdbc122779b13f0ff8
- Size of remote file:
- 115 MB
- SHA256:
- a17bec401ab6b289dbb27f89f373305a700cb7fd1defa64df479ad465ff09505
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