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---
title: README
emoji: 🪖
colorFrom: green
colorTo: black
sdk: static
pinned: false
---
<div class="grid lg:grid-cols-3 gap-x-4 gap-y-7">
<p class="lg:col-span-3">
Datatrooper is a Colombia based project that looks to implement state of the art technologies on local companies. <strong
>train and deploy Hugging Face models in Amazon SageMaker</strong
>.
</p>
<a
href="https://www.instagram.com/datatrooper/"
class="block overflow-hidden group"
>
<div
class="w-full h-30 object-cover mb-2 bg-indigo-100 rounded-lg flex items-center justify-center dark:bg-gray-900 dark:group-hover:bg-gray-850"
>
<img
alt=""
src="https://seeklogo.com/images/I/instagram-new-2016-logo-4773FE3F99-seeklogo.com.png"
class="w-40"
/>
</div>
<div class="underline">Read announcement blog post</div>
</a>
<a href="https://twitter.com/Datatrooper1" class="block overflow-hidden">
<img
alt=""
src="https://upload.wikimedia.org/wikipedia/commons/thumb/4/4f/Twitter-logo.svg/1200px-Twitter-logo.svg.png"
class="w-full h-30 object-cover mb-2 bg-gray-300 rounded-lg"
/>
<div class="underline">Video Walkthrough with Philipp Schmid</div>
</a>
<a
href="https://datatrooper.github.io/intro/"
class="block overflow-hidden group"
>
<div
class="w-full h-30 object-cover mb-2 bg-gray-900 group-hover:bg-gray-850 rounded-lg flex items-start justify-start"
>
<img
alt=""
src="https://pbs.twimg.com/media/EbEi9tYXkAEvfGj.jpg"
class="w-full h-30 object-cover mb-2 bg-gray-300 rounded-lg"
/>
</div>
<div class="underline">Documentation: Hugging Face in SageMaker</div>
</a>
<div class="lg:col-span-3">
<p class="mb-2">
To train Hugging Face models in Amazon SageMaker, you can use the
Hugging Face Deep Learning Contrainers (DLCs) and the Hugging Face
support in the SageMaker Python SDK.
</p>
<p class="mb-2">
The DLCs are fully integrated with the SageMaker distributed training
libraries to train models more quickly using the latest generation of
accelerated computing instances available on Amazon EC2. With the
SageMaker Python SDK, you can start training with just a single line of
code, enabling your teams to move from idea to production more quickly.
</p>
<p class="mb-2">
To deploy Hugging Face models in Amazon SageMaker, you can use the
Hugging Face Deep Learning Containers with the new Hugging Face
Inference Toolkit.
</p>
<p class="mb-2">
With the new Hugging Face Inference DLCs, deploy your trained models for
inference with just one more line of code, or select any of the 10,000+
models publicly available on the 🤗 Hub, and deploy them with Amazon
SageMaker, to easily create production-ready endpoints that scale
seamlessly, with built-in monitoring and enterprise-level security.
</p>
<p>
More information: <a
href="https://aws.amazon.com/blogs/machine-learning/aws-and-hugging-face-collaborate-to-simplify-and-accelerate-adoption-of-natural-language-processing-models/"
class="underline">AWS blog post</a
>,
<a
href="https://discuss.huggingface.co/c/sagemaker/17"
class="underline">Community Forum</a
>
</p>
</div>
</div>
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