Instructions to use facebook/convnext-tiny-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnext-tiny-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnext-tiny-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-tiny-224") model = AutoModelForImageClassification.from_pretrained("facebook/convnext-tiny-224", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from facebook/convnext-tiny-224: direct link, hf CLI and curl.
- Browser
- Download file 114 MB
-
https://huggingface.co/facebook/convnext-tiny-224/resolve/refs%2Fpr%2F3/flax_model.msgpack
- Command line
-
hf download hf://facebook/convnext-tiny-224@refs/pr/3/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/facebook/convnext-tiny-224/resolve/refs%2Fpr%2F3/flax_model.msgpack
114 MB
- Xet hash:
- 2e8fcb2995a3b7dd6a8840456d1cab33b6a3bec04701584f65e4c8199008034b
- Size of remote file:
- 114 MB
- SHA256:
- 208663e3fae809abbc5e43e234cfa712776c140f37b9841f26ea03819d769f86
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