Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Augusto777/vit-base-patch16-224-RXL1-24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Augusto777/vit-base-patch16-224-RXL1-24 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Augusto777/vit-base-patch16-224-RXL1-24") 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-RXL1-24") model = AutoModelForImageClassification.from_pretrained("Augusto777/vit-base-patch16-224-RXL1-24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Augusto777/vit-base-patch16-224-RXL1-24: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/Augusto777/vit-base-patch16-224-RXL1-24/resolve/main/training_args.bin
- Command line
-
hf download hf://Augusto777/vit-base-patch16-224-RXL1-24/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Augusto777/vit-base-patch16-224-RXL1-24/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 3e3b0e42d958fdd2edff485041ef2d1853276be872b281639b995ad2babd2d2a
- Size of remote file:
- 4.73 kB
- SHA256:
- 32fe5a97a9ee0e98a61e9c5af47a7800d0c437780fbb3144247325c8db05c215
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