Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Yudsky/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yudsky/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Yudsky/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("Yudsky/image_classification") model = AutoModelForImageClassification.from_pretrained("Yudsky/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aac83bb66e047ff03c4b2f035f186a0aa990612684b80434a1e0f38a41218c1f
- Size of remote file:
- 343 MB
- SHA256:
- 04a6b02e1acc54a6975a2a7ec1afb8c4594c99dc0131b9a96397fe4b2dc91dba
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