Instructions to use facebook/convnextv2-base-1k-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnextv2-base-1k-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnextv2-base-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-base-1k-224") model = AutoModelForImageClassification.from_pretrained("facebook/convnextv2-base-1k-224") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d235320cb20f86e280ca593e8995b610419bcc73b923ad8458ea35badb8437b6
- Size of remote file:
- 355 MB
- SHA256:
- 2f3867937d9254513f4c830f141e6f56215c769c7e0ae895329893b5ae1d8e5c
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