Instructions to use google/vit-large-patch32-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-large-patch32-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="google/vit-large-patch32-384") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("google/vit-large-patch32-384") model = AutoModelForImageClassification.from_pretrained("google/vit-large-patch32-384") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9b9d68deda21eced0a77a535def440e8e98b90e92d5738a601a045c09c95918
- Size of remote file:
- 1.23 GB
- SHA256:
- 0f6e29995103f8d05bbdc476dff934c2699798f1461bc59305e86c989876262b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.