How to Improve your LLM? Find the Best & Cheapest Solution

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): learn.activeloop.ai/courses/l...
With the great support of Cohere & Lambda.
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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

[@mohankrishnan08]

Amazing Explanation Louis,
Really thanks for this video.

[@jayanthacharya449]

Great explanation. Thanks for this.

[@YosmelLGD]

Thank you for the video ,we are going to build a llm from the scratch for businesses but I’m not sure if we would line to use others people data

[@micbab-vg2mu]

Thank you for the video.

[@ojasvisingh786]

👏👏

[@the_data_panda]

Feels like watching a huge ad for his courses, good info but the content of the videos can be structured better.

[@WhatsAI]

Thanks for the feedback. Could you help me understand how the structure could be improved here specifically for example? :)