Instructions to use aalonso-developer/vit-base-clothing-leafs-example 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 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") 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("aalonso-developer/vit-base-clothing-leafs-example") model = AutoModelForImageClassification.from_pretrained("aalonso-developer/vit-base-clothing-leafs-example", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aalonso-developer/vit-base-clothing-leafs-example: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/aalonso-developer/vit-base-clothing-leafs-example/resolve/main/training_args.bin
- Command line
-
hf download hf://aalonso-developer/vit-base-clothing-leafs-example/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aalonso-developer/vit-base-clothing-leafs-example/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 3f8cdbae8cc2ebc9448b60371652dd925635afaf5de95080b36c305705ae3d5f
- Size of remote file:
- 3.96 kB
- SHA256:
- b7b463a8aaadbbcc5d2b3445b05ee1ea10eb220661fcff3e196b5edcb10db1cb
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