Image Classification
Transformers
TensorBoard
Safetensors
swinv2
Generated from Trainer
Eval Results (legacy)
Instructions to use jayanthspratap/vit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayanthspratap/vit-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jayanthspratap/vit-base-patch16-224") 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("jayanthspratap/vit-base-patch16-224") model = AutoModelForImageClassification.from_pretrained("jayanthspratap/vit-base-patch16-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jayanthspratap/vit-base-patch16-224: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/jayanthspratap/vit-base-patch16-224/resolve/main/training_args.bin
- Command line
-
hf download hf://jayanthspratap/vit-base-patch16-224/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jayanthspratap/vit-base-patch16-224/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- b0982531c6c1de5fa261ca3b0c70cde17c332f931e22aafecfac9223ef9e682d
- Size of remote file:
- 5.11 kB
- SHA256:
- 7839f9a870927fc61aab987d04f12bac570cbbfd77409e11edc2dc9ca824f1da
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