Instructions to use facebook/convnext-base-224-22k-1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnext-base-224-22k-1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnext-base-224-22k-1k") 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/convnext-base-224-22k-1k") model = AutoModelForImageClassification.from_pretrained("facebook/convnext-base-224-22k-1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07cf545abac5c1653d478c5aabd1c89da85567513a2ed2ce5c814719cc89bde9
- Size of remote file:
- 354 MB
- SHA256:
- f53e2f2ed9ec98e1dc1d5dbca8fb0127d1efcecc4a2c2e7285052f45a6cb7512
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