Lessons from Nvidia Minitron
Pruning and Distillation Best Practices
We’d all love to build a model from scratch like Llama, but how realistic is that? The computing, architecture, and training data they have access to are so vast that it’s fair to say most of us wouldn’t be able to replicate it. But is it really necessary to train such large models from scratch anyway? What if the big companies just created one big model, and then we, the normal people, could use it to train smaller models that each of us would use for our specific tasks or data? Well, that’s exactly Llama’s goal with the release of the 405B model and leveraging distillation to train the smaller ones. Likewise, Nvidia recently released two papers that explore this exact amazing idea with their Minitron approach.
Good morning, everyone! I’m Louis-Francois, the CTO and Co-Founder of Towards AI, and this week, we’ll discuss the basics of knowledge distillation and the other techniques like pruning and quantization that can help you build models with limited resources...
This is video 9/10 of the "From Beginner to Advanced LLM Developer" course by Towards AI (discussed below).
Watch the video (or read the article here):
Discover the Skills You Need to Thrive in AI Development! This is the second video in our "From Beginner to Advanced LLM Developer" series by Towards AI, part of an 85+ lesson hands-on course designed to take you from zero to building scalable, cutting-edge LLM products.
Whether you're a software developer, ML engineer, aspiring entrepreneur, or an AI/CS student, this course gives you the real-world expertise to build, deploy, and manage advanced AI solutions. You'll work with tools like Python, OpenAI, LlamaIndex, Gradio, and others, while gaining invaluable insights into the entrepreneurial mindset and communication skills unique to the AI world.
💡 What makes this course stand out?
Build your first advanced AI product and portfolio-worthy projects.
Learn practical LLM skills like Prompting, RAG, Fine-Tuning, and Agent Design.
Industry-aligned lessons to help you transition into high-demand LLM developer roles or scale AI innovation in your company.
This journey goes beyond code—it’s a roadmap to making your competitive edge with tons of information on the future of AI development, which we termed "LLM developer."
🎯 Ready to take the leap? Check out the course here and don’t forget to explore our book (or e-book), Building LLMs for Production, for an even deeper dive into the LLM revolution.
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Thank you for reading, and I wish you a fantastic week! Be sure to have enough sleep and physical activities next week!
Louis-François Bouchard