Instructions to use facebook/convnextv2-tiny-22k-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnextv2-tiny-22k-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnextv2-tiny-22k-384") 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-22k-384") model = AutoModelForImageClassification.from_pretrained("facebook/convnextv2-tiny-22k-384", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60b511e5c307ae4b11db654e643e30887ba60d30cef3d469516f0b1f92e5d8f5
- Size of remote file:
- 115 MB
- SHA256:
- 3d19a0b02bfdc8396e24def16d6f6acfee0715efeb99231f237619b7e86d6787
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