Instructions to use google/vit-large-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-large-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="google/vit-large-patch16-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("google/vit-large-patch16-224", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12bc29a482a2e6a9c51ed53ccd7809b762f0d93792638f43c101ad56d0866f75
- Size of remote file:
- 1.22 GB
- SHA256:
- 13a547a1aef34fded515d672219962d637cdce195788a08c9e233129c1cc0272
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.