Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use syaha/Image-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syaha/Image-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="syaha/Image-Classification") 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("syaha/Image-Classification") model = AutoModelForImageClassification.from_pretrained("syaha/Image-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a4806aa7382eadf3c80e0becbc53ad27c1a9d8f7031a2cc514b2d544bdd6f78
- Size of remote file:
- 343 MB
- SHA256:
- 5f96e392632eabcef2dadde997a700b6da70e766f737ee60dbfb221bb31ce966
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