Image Classification
Transformers
TensorBoard
Safetensors
cvt
Generated from Trainer
Eval Results (legacy)
Instructions to use andrecastro/cvt-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andrecastro/cvt-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="andrecastro/cvt-13") 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("andrecastro/cvt-13") model = AutoModelForImageClassification.from_pretrained("andrecastro/cvt-13") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1fc6f09b20039024c21c77f4c84345ea0b553ddadbca60437cc740c4dc836f4
- Size of remote file:
- 4.6 kB
- SHA256:
- 1f286a05ded062162f0eec671fd0ce2949c21109d5ad8dec4d369e39170c1829
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