Instructions to use facebook/convnext-base-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnext-base-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnext-base-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/convnext-base-224") model = AutoModelForImageClassification.from_pretrained("facebook/convnext-base-224", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/convnext-base-224: direct link, hf CLI and curl.
- Browser
- Download file 354 MB
-
https://huggingface.co/facebook/convnext-base-224/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/convnext-base-224/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/convnext-base-224/resolve/main/pytorch_model.bin
354 MB
- Xet hash:
- 74627c44dcb8bfb260600d25ff7ad48b98b4204746040fa651f934f68b9b80e3
- Size of remote file:
- 354 MB
- SHA256:
- cb0a2fc07b6ed8e6725911c7072408e374ba0a86e6cdf0ad7d105153b62b507d
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