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app.py
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@@ -2,7 +2,7 @@ import streamlit as st
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# Quickstart
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%% [markdown]
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# This quickstart is intended for developers who are ready to dive into the code and see an example of how to integrate Datasets into their model training workflow. If you're a beginner, we recommend starting with our [tutorials](https://huggingface.co/docs/datasets/main/en/./tutorial), where you'll get a more thorough introduction.
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# Each dataset is unique, and depending on the task, some datasets may require additional steps to prepare it for training. But you can always use datasets tools to load and process a dataset. The fastest and easiest way to get started is by loading an existing dataset from the [Hugging Face Hub](https://huggingface.co/datasets). There are thousands of datasets to choose from, spanning many tasks. Choose the type of dataset you want to work with, and let's get started!
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# Quickstart
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# %% [markdown]
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# This quickstart is intended for developers who are ready to dive into the code and see an example of how to integrate Datasets into their model training workflow. If you're a beginner, we recommend starting with our [tutorials](https://huggingface.co/docs/datasets/main/en/./tutorial), where you'll get a more thorough introduction.
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# Each dataset is unique, and depending on the task, some datasets may require additional steps to prepare it for training. But you can always use datasets tools to load and process a dataset. The fastest and easiest way to get started is by loading an existing dataset from the [Hugging Face Hub](https://huggingface.co/datasets). There are thousands of datasets to choose from, spanning many tasks. Choose the type of dataset you want to work with, and let's get started!
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