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Add Lightning Studios to Cloud Partners
Signed-off-by: Chris Abraham <[email protected]>
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_get_started/get-started-via-cloud-partners.md

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{% include_relative installation/google-cloud.md %}
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{% endcapture %}
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{% capture google-cloud %}
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{% include_relative installation/lightning-studios.md %}
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{% endcapture %}
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<div id="cloud">
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<div class="platform aws">{{aws | markdownify }}</div>
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# Using PyTorch with Lightning Studios
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{:.no_toc}
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Lightning Studios let you fully experience PyTorch and its ecosystem on accelerated compute in seconds. You can pick a GPU and customize from your browser or any local IDE with zero setup.
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**Lightning Studios provide:**
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* ready-to-use environments that come with PyTorch and PyTorch Lightning pre-installed
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* accelerated computing on GPUs such as L4, L40S, and H100, and the ability to switch between them in seconds
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* optimized multi-node training, to scale up PyTorch training jobs across machines
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Lightning Studios enable you to share fully reproducible environments preloaded with everything you need to build AI systems, like data processing, pretraining, finetuning, inference, etc. Our library of 2K community-built, open sourced templates have pre-installed dependencies, model weights, data, code and more.
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## Getting Started
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{: #ls-getting-started}
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* Go to [lightning.ai](http://lightning.ai/)
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* Sign up (you get 22 free GPU hours monthly)
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* Start up your first Studio
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* Or duplicate one of our templates at [lightning.ai/studios](http://lightning.ai/studios)
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**With Studios, you can:**
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* Pay-as-you-go
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* Get GPUs from $0.40 p/h
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* Use your own AWS credits
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* Access 24/7 Enterprise support
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## Build AI, not infrastructure
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{: #ls-build}
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With Lightning Studios, you can easily build AI products with full and low code tools in one place, plus access GPUs, train models and deploy.
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AI products like Stable Diffusion and NVIDIA’s NeMo are built with Lightning. Whether you're experimenting with your first model, AI app, or deploying AI at enterprise scale. Lightning powers every stage — even pretraining LLMs on 10,000+ GPUs.

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