Instructions to use facebook/convnextv2-nano-22k-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnextv2-nano-22k-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnextv2-nano-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-nano-22k-384") model = AutoModelForImageClassification.from_pretrained("facebook/convnextv2-nano-22k-384", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbe0de58fec98799188b9e0c84828f896689d6f0b972ea69430678b2debf7e0a
- Size of remote file:
- 62.5 MB
- SHA256:
- 79620293dde7f8d5e635dc93ec41848aeaa3f02d731680b5cfb7901bc1252302
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