In this video, we dive into the world of large language models (LLMs) and discover the optimal techniques for your specific tasks! Learn when to choose between training from scratch, fine-tuning, (advanced) prompt engineering and Retrieval Augmented Generation (RAG) with Activeloop’s Deep Memory. Equip yourself with the knowledge to enhance LLM performance, balancing quality, costs, and ease of use. ✨🚀
► Jump on our free LLM course from the Gen AI 360 Foundational Model Certification (Built in collaboration with Activeloop, Towards AI, and the Intel Disruptor Initiative): https://learn.activeloop.ai/courses/llms/?utm_source=social&utm_medium=youtube&utm_campaign=llmcourse
With the great support of Cohere & Lambda.
► Course Official Discord: https://discord.gg/learnaitogether
► Activeloop Slack: https://slack.activeloop.ai/
► Activeloop YouTube: https://www.youtube.com/@activeloop
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How to start in AI/ML – A Complete Guide:
►https://www.louisbouchard.ai/learnai/
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Chapters:
0:00 When do what with LLMs?
0:20 What are the techniques available?
1:24 Improve your model with prompt engineering!
2:12 RAG and Deep Memory!
3:04 Fine-tuning LLMs (LoRa and QLoRa).
5:41 Training from scratch.
8:20 Conclusion.
#ai #languagemodels #llm
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