Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use sabrilben/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sabrilben/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sabrilben/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("sabrilben/image_classification") model = AutoModelForImageClassification.from_pretrained("sabrilben/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74c214bd2410f51c5874fd6ef316ada6d07713e83428860301a9a13b13b0634a
- Size of remote file:
- 5.37 kB
- SHA256:
- ebe66e61d07378d8c93d8bda5c54d2feb27379653fe05cf077109560cf787f22
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