| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': '0' | |
| '1': '1' | |
| '2': '2' | |
| '3': '3' | |
| '4': '4' | |
| '5': '5' | |
| '6': '6' | |
| '7': '7' | |
| '8': '8' | |
| '9': '9' | |
| - name: source_index | |
| dtype: int32 | |
| splits: | |
| - name: train | |
| num_bytes: 17155689 | |
| num_examples: 60000 | |
| - name: test | |
| num_bytes: 2555832 | |
| num_examples: 8920 | |
| download_size: 19348835 | |
| dataset_size: 19711521 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: test | |
| path: data/test-* | |
| # tsilva/mnist | |
| ## Dataset Summary | |
| This dataset is a Hugging Face packaged version of the classic MNIST handwritten digits benchmark. It contains grayscale 28x28 images of digits `0` through `9`, split into the standard `train` and `test` partitions. | |
| Each row includes: | |
| - `image`: a 28x28 grayscale digit image | |
| - `label`: the digit class from `0` to `9` | |
| - `source_index`: the original position of the example inside the source MNIST split | |
| ## Splits | |
| - `train`: 60,000 examples | |
| - `test`: 8,920 examples, balanced to `892` examples per class | |
| ## Source | |
| The underlying data comes from the original MNIST release maintained by Yann LeCun and collaborators and downloaded here through `torchvision.datasets.MNIST`. | |
| - MNIST homepage: http://yann.lecun.com/exdb/mnist/ | |
| - TorchVision dataset docs: https://pytorch.org/vision/stable/generated/torchvision.datasets.MNIST.html | |
| ## Intended Use | |
| This dataset is suitable for standard handwritten digit classification baselines, representation learning experiments, and as a clean reference set for synthetic corruption studies. | |
| ## Load Example | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("tsilva/mnist") | |
| print(ds["train"][0]) | |
| ``` | |