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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Renaming *.grn.gamma -> *.grn.weight, *.grn.beta -> *.grn.bias and adding `safetensors` variant of this model (#4)
Verified signature- Renaming *.grn.gamma -> *.grn.weight, *.grn.beta -> *.grn.bias and adding `safetensors` variant of this model (3c72ae63e4ff47938a74cef6f49bb723fd769904) Co-authored-by: Ross Wightman <rwightman@users.noreply.huggingface.co>f4db009
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Upload ConvNextV2ForImageClassification
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