Instructions to use facebook/convnextv2-huge-22k-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnextv2-huge-22k-512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnextv2-huge-22k-512") 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-huge-22k-512") model = AutoModelForImageClassification.from_pretrained("facebook/convnextv2-huge-22k-512", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/convnextv2-huge-22k-512: direct link, hf CLI and curl.
- Browser
- Download file 2.64 GB
-
https://huggingface.co/facebook/convnextv2-huge-22k-512/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/convnextv2-huge-22k-512/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/convnextv2-huge-22k-512/resolve/main/pytorch_model.bin
2.64 GB
- Xet hash:
- 806a37dd290abaec4f71f96a3fa102568972d0237e432da5244406e3a048da86
- Size of remote file:
- 2.64 GB
- SHA256:
- 6e3364c6a0bfc1a520b7a7826781cbe213116db88dd721e1c8dd5308aa965f4e
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