Instructions to use pawlo2013/kimchi-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pawlo2013/kimchi-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pawlo2013/kimchi-classification") 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("pawlo2013/kimchi-classification") model = AutoModelForImageClassification.from_pretrained("pawlo2013/kimchi-classification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:89996ee1ed6a37a1968c93c64c135a2de6add8ec3c334294940c2318465734a8
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size 343251660
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