Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
mnist
handwritten-digits
Generated from Trainer
Instructions to use Fadri/mnist-digit-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fadri/mnist-digit-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Fadri/mnist-digit-recognition") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Fadri/mnist-digit-recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +0 -8
config.json
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{
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// Name deiner Klasse, wenn du willst
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"architectures": ["MNISTModel"],
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// Damit HF weiß, mit welchem Pipeline-Typ es das zu tun hat
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// Hier nehmen wir “image-classification”
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"model_type": "image-classification",
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// Anzahl der Output-Klassen in deinem CNN
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"num_labels": 10,
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// Optional: weitere Infos, z.B. Input-Formate
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"image_size": [28, 28]
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}
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{
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"architectures": ["MNISTModel"],
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"model_type": "image-classification",
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"num_labels": 10,
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"image_size": [28, 28]
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}
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