Instructions to use shubhamsingh123/mnist-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use shubhamsingh123/mnist-model with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://shubhamsingh123/mnist-model") - Notebooks
- Google Colab
- Kaggle
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Download sample_data/README.md from shubhamsingh123/mnist-model: direct link, hf CLI and curl.
- Browser
- Download file 962 Bytes
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https://huggingface.co/shubhamsingh123/mnist-model/resolve/main/sample_data/README.md
- Command line
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hf download hf://shubhamsingh123/mnist-model/sample_data/README.md
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curl -L -o README.md https://huggingface.co/shubhamsingh123/mnist-model/resolve/main/sample_data/README.md
962 Bytes
| This directory includes a few sample datasets to get you started. | |
| * `california_housing_data*.csv` is California housing data from the 1990 US | |
| Census; more information is available at: | |
| https://docs.google.com/document/d/e/2PACX-1vRhYtsvc5eOR2FWNCwaBiKL6suIOrxJig8LcSBbmCbyYsayia_DvPOOBlXZ4CAlQ5nlDD8kTaIDRwrN/pub | |
| * `mnist_*.csv` is a small sample of the | |
| [MNIST database](https://en.wikipedia.org/wiki/MNIST_database), which is | |
| described at: http://yann.lecun.com/exdb/mnist/ | |
| * `anscombe.json` contains a copy of | |
| [Anscombe's quartet](https://en.wikipedia.org/wiki/Anscombe%27s_quartet); it | |
| was originally described in | |
| Anscombe, F. J. (1973). 'Graphs in Statistical Analysis'. American | |
| Statistician. 27 (1): 17-21. JSTOR 2682899. | |
| and our copy was prepared by the | |
| [vega_datasets library](https://github.com/altair-viz/vega_datasets/blob/4f67bdaad10f45e3549984e17e1b3088c731503d/vega_datasets/_data/anscombe.json). | |