Instructions to use facebook/convnextv2-large-22k-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnextv2-large-22k-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnextv2-large-22k-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-large-22k-224") model = AutoModelForImageClassification.from_pretrained("facebook/convnextv2-large-22k-224", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/convnextv2-large-22k-224: direct link, hf CLI and curl.
- Browser
- Download file 792 MB
-
https://huggingface.co/facebook/convnextv2-large-22k-224/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/convnextv2-large-22k-224/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/convnextv2-large-22k-224/resolve/main/pytorch_model.bin
792 MB
- Xet hash:
- 764d7af69696e77bd6ec620c124a170cd8f41aa891b5c0e2cf320666fa76e75d
- Size of remote file:
- 792 MB
- SHA256:
- b52971c5bf9b36b41b966030a75684ec93b83fc22f176599bcb5ce9758a0e5f9
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