Instructions to use nathanReitinger/FASHION-vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nathanReitinger/FASHION-vision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nathanReitinger/FASHION-vision") 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("nathanReitinger/FASHION-vision") model = AutoModelForImageClassification.from_pretrained("nathanReitinger/FASHION-vision", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_trainer
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metrics:
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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datasets:
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- fashion_mnist
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tags:
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- generated_from_trainer
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metrics:
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