Instructions to use google/vit-huge-patch14-224-in21k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-huge-patch14-224-in21k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="google/vit-huge-patch14-224-in21k")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("google/vit-huge-patch14-224-in21k") model = AutoModel.from_pretrained("google/vit-huge-patch14-224-in21k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74fbd773398234c5a306364ed72690d95f71ad4cd5385f25d455d0412d23ded1
- Size of remote file:
- 2.53 GB
- SHA256:
- 205cb171f212547101e11ddbb546505b77844e6070639b8b4d5dafccc9b01802
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.