Instructions to use pphildan/vit-base-patch16-224-v21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pphildan/vit-base-patch16-224-v21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pphildan/vit-base-patch16-224-v21") 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("pphildan/vit-base-patch16-224-v21") model = AutoModelForImageClassification.from_pretrained("pphildan/vit-base-patch16-224-v21", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from pphildan/vit-base-patch16-224-v21: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/pphildan/vit-base-patch16-224-v21/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://pphildan/vit-base-patch16-224-v21@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pphildan/vit-base-patch16-224-v21/resolve/refs%2Fpr%2F1/pytorch_model.bin
343 MB
- Xet hash:
- cb291de50c9e587ede005094f9bad6528f0b77d7c1c3d3d23544cd6dfb417c25
- Size of remote file:
- 343 MB
- SHA256:
- 683242a41e14b792c507ba2de6913a84e44b599a9e69e6566e070255a51f557a
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