Update README.md

README.md

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-<p class="lg:col-span-3">
-	Hugging Face is working with Amazon Web Services to make it easier than
-	ever for startups and enterprises to <strong
-		>train and deploy Hugging Face models in Amazon SageMaker</strong
-	>.
-</p>
-<a
-	href="https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face"
-	class="block overflow-hidden group"
->
-	<div
-		class="w-full h-40 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="/front/assets/promo/amazon_sagemaker_x_huggingface.png"
-			class="w-40"
-		/>
-	</div>
-	<div class="underline">Read announcement blog post</div>
-</a>
-<a href="https://youtu.be/ok3hetb42gU" class="block overflow-hidden">
-	<img
-		alt=""
-		src="/front/assets/promo/amazon_walkthrough_thumbnail.png"
-		class="w-full h-40 object-cover mb-2 bg-gray-300 rounded-lg"
-	/>
-	<div class="underline">Video Walkthrough with Philipp Schmid</div>
-</a>
-<a
-	href="https://huggingface.co/docs/sagemaker"
-	class="block overflow-hidden group"
->
-	<div
-		class="w-full h-40 object-cover mb-2 bg-gray-900 group-hover:bg-gray-850 rounded-lg flex items-start justify-start"
-	>
-		<img
-			alt=""
-			src="/front/assets/promo/amazon_documentation.png"
-			class="w-44 p-4"
-		/>
-	</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>
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