Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use goodcasper/vit_itri_2class_downsample with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use goodcasper/vit_itri_2class_downsample with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="goodcasper/vit_itri_2class_downsample") 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("goodcasper/vit_itri_2class_downsample") model = AutoModelForImageClassification.from_pretrained("goodcasper/vit_itri_2class_downsample") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69b53766bf406db30e571d42b943af60b6f34985ac88328ba42c3002d2d79c1c
- Size of remote file:
- 5.71 kB
- SHA256:
- c0784659c41cab313cc16c7cdd09d0a3796972c0c58140b2ff671a1029bf93d9
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