Instructions to use Augusto777/vit-base-patch16-224-RX2-24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Augusto777/vit-base-patch16-224-RX2-24 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Augusto777/vit-base-patch16-224-RX2-24") 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("Augusto777/vit-base-patch16-224-RX2-24") model = AutoModelForImageClassification.from_pretrained("Augusto777/vit-base-patch16-224-RX2-24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Augusto777/vit-base-patch16-224-RX2-24: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/Augusto777/vit-base-patch16-224-RX2-24/resolve/main/training_args.bin
- Command line
-
hf download hf://Augusto777/vit-base-patch16-224-RX2-24/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Augusto777/vit-base-patch16-224-RX2-24/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 793e9dbafcfc8d4d15fbb47c35f1ca9dac01f3e7328fa9d2523b2205cb9cf889
- Size of remote file:
- 4.73 kB
- SHA256:
- 9e6451551ecf2e4f3f0feffd089a9fe52109e23bc56298d3b5f15373a8349327
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