<FrameworkSwitchCourse {fw} />

# Introduction[[introduction]]

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    chapter={3}
    classNames="absolute z-10 right-0 top-0"
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In [Chapter 2](/course/chapter2) we explored how to use tokenizers and pretrained models to make predictions. But what if you want to fine-tune a pretrained model for your own dataset? That's the topic of this chapter! You will learn:

{#if fw === 'pt'}
* How to prepare a large dataset from the Hub
* How to use the high-level `Trainer` API to fine-tune a model
* How to use a custom training loop
* How to leverage the 🤗 Accelerate library to easily run that custom training loop on any distributed setup

{:else}
* How to prepare a large dataset from the Hub
* How to use Keras to fine-tune a model
* How to use Keras to get predictions
* How to use a custom metric

{/if}

In order to upload your trained checkpoints to the Hugging Face Hub, you will need a huggingface.co account: [create an account](https://huggingface.co/join)