Image Classification
Transformers
TensorBoard
Safetensors
vit
LMH
3_class
VIT
Generated from Trainer
Instructions to use Shinee21/ViT_beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shinee21/ViT_beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Shinee21/ViT_beans") 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("Shinee21/ViT_beans") model = AutoModelForImageClassification.from_pretrained("Shinee21/ViT_beans") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8bab5d842f8399f6c16e10805ab3c2f254405995483cc67d933a8365a70182a1
- Size of remote file:
- 343 MB
- SHA256:
- 3bdc8585c71db97de9cf45ac40205a5152b8d4440a86d49afa78248f1689735e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.