Instructions to use DaniServin/vit_model0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DaniServin/vit_model0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DaniServin/vit_model0") 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("DaniServin/vit_model0") model = AutoModelForImageClassification.from_pretrained("DaniServin/vit_model0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fca3c907059d351ae947dcffae3124abcfdcb12e79560dbb97fa114a4e6b884f
- Size of remote file:
- 5.3 kB
- SHA256:
- 85adea844b0e7b6b8edb878b07556668ca06186f5a94f5ec595d32c7facbd743
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