Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use yeonghun2/clasfy_error with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yeonghun2/clasfy_error with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="yeonghun2/clasfy_error") 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("yeonghun2/clasfy_error") model = AutoModelForImageClassification.from_pretrained("yeonghun2/clasfy_error", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download images/normal.png from yeonghun2/clasfy_error: direct link, hf CLI and curl.
- Browser
- Download file 663 kB
-
https://huggingface.co/yeonghun2/clasfy_error/resolve/main/images/normal.png
- Command line
-
hf download hf://yeonghun2/clasfy_error/images/normal.png
-
curl -L -o normal.png https://huggingface.co/yeonghun2/clasfy_error/resolve/main/images/normal.png
663 kB

- Xet hash:
- e5414a552616d7eb500a5bfc413865accfdc74f2380fd6404b1b66543be9e56d
- Size of remote file:
- 663 kB
- SHA256:
- dd80160eb93730f20141f55bd057e9c71f77683f3eef5ceebd7bc1284d4b65d4
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