How to Improve your LLM?
Find the Best & Cheapest Solution to boost LLM performances
Good morning fellow AI enthusiast! This is the fifth iteration of my video series for our free course "Training & Fine-Tuning LLMs for Production"!
In this one, we dive into the world of large language models (LLMs) and discover the optimal techniques for your specific tasks!
Learn the ins and outs of training from scratch, fine-tuning, and prompt engineering, including Few-Shot Learning and Retrieval Augmented Generation (RAG).
Everything to enhance LLM performance, balancing quality, costs, and ease of use. ✨🚀
1️⃣ How to Improve your LLM? Find the Best & Cheapest Solution
Retrieval Augmented Generation (RAG) is now extremely popular. But what's the difference with fine-tuning or simple "prompting" or even training entirely from scratch? When should you use what?
Either launch a fast GPT-4 and explore prompt engineering and once needed try out fine-tuning for style-specific LLM adaptation without full retraining.
If you see lots of model hallucinations and/or misaligned output, try out RAG to enhance model accuracy and knowledge.
When it comes to fine-tuning, explore low-cost fine-tuning with LoRa and QLoRa. In the video and our free course (below), we cover large-scale model refinement and discuss training a model from scratch, including required datasets and resources.
This video guides developers and AI enthusiasts on improving LLMs, offering methods for both minor and major advancements. Watch to refine LLM optimization skills:
2️⃣ More about our course in collaboration with Towards AI , Activeloop , and the Intel Corporation disruptor initiative!
Tl;dr: The course is about showing everything about LLMs (train, fine-tune, use RAG…), and it is completely free!
Is the course for you?
If you want to learn how to train and fine-tune LLMs from scratch, and have intermediate Python knowledge, you should be all set to take and complete the course.
This course is designed with a wide audience in mind, including beginners in AI, current machine learning engineers, students, and professionals considering a career transition to AI.
We aim to provide you with the necessary tools to apply and tailor Large Language Models across a wide range of industries to make AI more accessible and practical.
Get your certificate doing the course!
And that's it for this iteration! I'm incredibly grateful that the What's AI newsletter is now read by over 14,000+ incredible human beings and counting. Share this iteration with a friend if you learned something new!
Looking for more cool AI stuff? 👇
Looking for AI news, code, learning resources, papers, memes, and more? Follow our newsletter at Towards AI, which is going out weekly!
Looking for other AI enthusiasts? Join my Discord community: Learn AI Together!
If you need more content to go through your week, check out the podcast!
Please reach out with any questions or details on sponsorships, or visit my Passionfroot profile to see my offers.
Thank you for reading, and we wish you a fantastic week! Be sure to have enough rest and sleep!
Louis-François Bouchard
Click here and send your custom link to your friends or on your socials!