Instructions to use aalonso-developer/vit-base-clothing-leafs-example-full-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aalonso-developer/vit-base-clothing-leafs-example-full-simple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="aalonso-developer/vit-base-clothing-leafs-example-full-simple") 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("aalonso-developer/vit-base-clothing-leafs-example-full-simple") model = AutoModelForImageClassification.from_pretrained("aalonso-developer/vit-base-clothing-leafs-example-full-simple") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a10ef991a9bbe2e52abd29939ceffd1fd77735e620c81318f148c6ce2c306dba
- Size of remote file:
- 4.03 kB
- SHA256:
- 78f0ebe398df03ac7432c1a457136102ea21cc8901449d33e582b52aa9d45dc5
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