Instructions to use Andron00e/ViTForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andron00e/ViTForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Andron00e/ViTForImageClassification") 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("Andron00e/ViTForImageClassification") model = AutoModelForImageClassification.from_pretrained("Andron00e/ViTForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Andron00e/ViTForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/Andron00e/ViTForImageClassification/resolve/main/training_args.bin
- Command line
-
hf download hf://Andron00e/ViTForImageClassification/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Andron00e/ViTForImageClassification/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- db737fd96e9039611b7affee74cf3d3deb6c699d74a3d090fd694cf3a3dd7762
- Size of remote file:
- 4.03 kB
- SHA256:
- 854e3c4628a163f131ec0772e3285593146796483981898253b10f4ec505016e
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