Instructions to use kraftman1/image_classification_ConvNext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kraftman1/image_classification_ConvNext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kraftman1/image_classification_ConvNext") 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("kraftman1/image_classification_ConvNext") model = AutoModelForImageClassification.from_pretrained("kraftman1/image_classification_ConvNext", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kraftman1/image_classification_ConvNext: direct link, hf CLI and curl.
- Browser
- Download file 111 MB
-
https://huggingface.co/kraftman1/image_classification_ConvNext/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kraftman1/image_classification_ConvNext/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kraftman1/image_classification_ConvNext/resolve/main/pytorch_model.bin
111 MB
- Xet hash:
- 0b53e5cc7d45a6b934b7fdd97505c729379d0ea9b5ec09a6f00446ecc6ab9e33
- Size of remote file:
- 111 MB
- SHA256:
- 5887984014ee3ced8479362319a5502c20b138ce2cc07dd5a91ba56ff26fd101
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