Instructions to use acbdkk/cifar10model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use acbdkk/cifar10model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="acbdkk/cifar10model") 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("acbdkk/cifar10model") model = AutoModelForImageClassification.from_pretrained("acbdkk/cifar10model") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -1
config.json
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"vocab_size": 30522,
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"type_vocab_size": 2,
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"max_position_embeddings": 512,
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"model_type": "
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}
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"vocab_size": 30522,
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"type_vocab_size": 2,
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"max_position_embeddings": 512,
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"model_type": "vit"
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}
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