Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Dimasnoufal/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dimasnoufal/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Dimasnoufal/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("Dimasnoufal/image_classification") model = AutoModelForImageClassification.from_pretrained("Dimasnoufal/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1dae922da86c8c0bb355424fa9bb94ee5526a2d480d9a879339fd57eda2c717
- Size of remote file:
- 343 MB
- SHA256:
- aadd85fda4c959730a8bd697cfd859f31789c4f9b8db41682e2fa1d831ce8887
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