Image Classification
Transformers
TensorBoard
Safetensors
vit
LMH
3_class
ViT
Generated from Trainer
Instructions to use HanDaeYu/ViT_beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HanDaeYu/ViT_beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HanDaeYu/ViT_beans") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("HanDaeYu/ViT_beans") model = AutoModelForImageClassification.from_pretrained("HanDaeYu/ViT_beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from HanDaeYu/ViT_beans: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/HanDaeYu/ViT_beans/resolve/main/training_args.bin
- Command line
-
hf download hf://HanDaeYu/ViT_beans/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/HanDaeYu/ViT_beans/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 3e41984236453ecd455775a112d7fb8957023a2d0aa7773f264d19e858076405
- Size of remote file:
- 5.18 kB
- SHA256:
- 694b53bec979066b266474f909a7df2a77bf270ce65b0591f8f088cce3392a60
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