Instructions to use google/vit-base-patch16-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-base-patch16-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="google/vit-base-patch16-384") 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-base-patch16-384") model = AutoModelForImageClassification.from_pretrained("google/vit-base-patch16-384", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
ac80a30 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:bdbac7b68edde2a8f13a4dd5d7230f7bd4a87368a123620facbc331808e353b9
size 347721408
|