Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use GGital/vit-SUPER02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GGital/vit-SUPER02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="GGital/vit-SUPER02") 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("GGital/vit-SUPER02") model = AutoModelForImageClassification.from_pretrained("GGital/vit-SUPER02") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7357b88afee5e174c5e38123b593156d7b442d77fb7cb4402de8f33128ae456
- Size of remote file:
- 4.73 kB
- SHA256:
- a0df834a064202344629829fe948dbefa8462af544011692fa35ffcc67a80fb5
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