Instructions to use venetis/convnext-tiny-224_album_vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use venetis/convnext-tiny-224_album_vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="venetis/convnext-tiny-224_album_vit") 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("venetis/convnext-tiny-224_album_vit") model = AutoModelForImageClassification.from_pretrained("venetis/convnext-tiny-224_album_vit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Size of remote file:
- 112 MB
- SHA256:
- 117fe60f1e82b3405caf88044c9b5d7d786f2ca57415d3bbab24617ea0cd6496
·
Git Large File Storage (LFS) replaces large files with text pointers inside Git, while storing the file contents on a remote server. More info.