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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 602ae32f3662f2c4639b9d5d6d8e9ccd3c7c6a79ecc608cfabdd3a0ebd30610f
- Size of remote file:
- 5.24 kB
- SHA256:
- 89f77cb00eda89be422b07e53294f5df416078cad761beb69ad72561276f375a
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