Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use ruben09/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruben09/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ruben09/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("ruben09/image_classification") model = AutoModelForImageClassification.from_pretrained("ruben09/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a713d036f3016dadb9b3ab77186cc122a4416ed758e92806e1a0cfaf0da77007
- Size of remote file:
- 343 MB
- SHA256:
- 273116a634d1e7cf55ab27cf5ab7755c56f3d5c66d4af624453aa9aac6d388a3
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