Instructions to use facebook/convnext-small-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnext-small-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnext-small-224") 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-small-224") model = AutoModelForImageClassification.from_pretrained("facebook/convnext-small-224") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 939771088a939e54c33b14123d88deafb7016690b7a311e207d4139d348a11c0
- Size of remote file:
- 201 MB
- SHA256:
- b3cbe154c1cb96aeff1fe8d0d4bd9808423ce941a9f70dac0ffe77f31abf9b83
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.