In this tutorial, we will explore the newly announced NVIDIA NIM platform and use it to create our very own Llama 3.1 Powered Application! 🤩🤩🤩
Specifically, we will dive into NIM's collection of inference microservices, and state of the art APIs! (it's OK if you're not sure what it means yet, I explain it in the video 😉)
The end result, is your own Custom Dataset Maker App that you can adjust and enhance with a little bit of Python! 🤓

This video is perfect for beginners, as I explain all the advanced AI concepts in simple language and with plenty of visual examples. It is also perfect for professionals, as I show you how to skip the entire AI pipeline setup with the help of NIM.

⭐ Checkout the NIM API Catalog Here:
[ Ссылка ]

⏰ Timestamps ⏰
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00:00 - intro
00:38 - what is NVIDIA NIM?
00:55 - what are microservices?
01:20 - microservices challenges
01:42 - NIM benefits
02:30 - NIM components
03:11 - what is an API?
03:54 - NIM API Catalog demo
05:10 - NIM deployment options
06:45 - generate NGC API KEY
07:51 - deploy NIM container
09:03 - model health check
09:31 - run basic Llama prompt code
10:37 - a heavy metal song about job search
11:09 - Llama request object
12:29 - Llama response object
13:40 - chain a series of prompts
16:22 - convert prompt response to list
17:45 - save custom dataset to CSV
18:14 - thanks for watching!

🚀 My Brev Launchable - Dataset Maker Notebook 🚀
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📺 Related Tutorials of Mine📺
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⭐ CUDA For Beginners:
[ Ссылка ]
⭐ Docker Containers Simply Explained:
[ Ссылка ]

🤝 Connect with me 🤝
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🔗 Github:
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🔗 X:
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🔗 LinkedIn:
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🔗 Blog:
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🔗 Discord:
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💳 Credits 💳
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⭐ Beautiful titles, transitions, sound FX:
mixkit.co
⭐ Beautiful Icons:
flaticon.com
⭐ Beautiful Thumbnail:
Grok and Firefly

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