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:
- 8960cea72cb3730edc872e8427a459e37e73fa6e744f31fd6ee0a96d7e429b62
- Size of remote file:
- 5.24 kB
- SHA256:
- 1a142f617595fc486d89d3f53672300f3ab16e4c745fec4c1fa0e0aec382d8ce
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