Instructions to use jerilseb/mnist-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jerilseb/mnist-classifier with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import MNISTClassifier model = MNISTClassifier.from_pretrained("jerilseb/mnist-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from jerilseb/mnist-classifier: direct link, hf CLI and curl.
- Browser
- Download file 639 Bytes
-
https://huggingface.co/jerilseb/mnist-classifier/resolve/main/config.json
- Command line
-
hf download hf://jerilseb/mnist-classifier/config.json
-
curl -L -o config.json https://huggingface.co/jerilseb/mnist-classifier/resolve/main/config.json
639 Bytes
| { | |
| "architectures": [ | |
| "MNISTClassifier" | |
| ], | |
| "hidden_size1": 1024, | |
| "hidden_size2": 512, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1", | |
| "2": "LABEL_2", | |
| "3": "LABEL_3", | |
| "4": "LABEL_4", | |
| "5": "LABEL_5", | |
| "6": "LABEL_6", | |
| "7": "LABEL_7", | |
| "8": "LABEL_8", | |
| "9": "LABEL_9" | |
| }, | |
| "input_size": 784, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1, | |
| "LABEL_2": 2, | |
| "LABEL_3": 3, | |
| "LABEL_4": 4, | |
| "LABEL_5": 5, | |
| "LABEL_6": 6, | |
| "LABEL_7": 7, | |
| "LABEL_8": 8, | |
| "LABEL_9": 9 | |
| }, | |
| "model_type": "mnist_classifier", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.42.3" | |
| } | |