LLM Ecosystem explained: Your ultimate Guide to AI

preview_player
Показать описание
Introduction to the world of LLM (Large Language Models) in April 2023. With detailed explanation of GPT-3.5, GPT-4, T5, Flan-T5 to LLama, Alpaca and KOALA LLM, plus dataset sources and configurations.
Including ICL (in-context learning), adapter fine-tuning, PEFT LoRA and classical fine-tuning of LLM explained. When to choose what type of data set for what LLM job?

Addendum: Beautiful, new open-source "DOLLY 2.0" LLM was not published at time of recording, therefore a special link to my video explaining DOLLY 2:

A comprehensive LLM /AI ecosystem is essential for the creation and implementation of sophisticated AI applications. It facilitates the efficient processing of large-scale data, the development of complex machine learning models, and the deployment of intelligent systems capable of performing complex tasks.

As the field of AI continues to evolve and expand, the importance of a well-integrated and cohesive AI ecosystem cannot be overstated.

A complete overview of today's LLM and how you can train them for your needs.

#naturallanguageprocessing
#LargeLanguageModels
#chatgpttutorial
#finetuning
#finetune
#ai
#introduction
#overview
#chatgpt
Рекомендации по теме
Комментарии
Автор

What an amazing video.
You compressed into less than 30 minutes what took me many many hours to learn and still my knowledge increased a lot with this video.

Thank you very much!

Esteband
Автор

Absolutely fantastic explanation and visualization about what’s happening! Thank you 🙏🏻

mtin
Автор

Just wanted to add my appreciation. This is an excellent overview for those interested in the possibilities without a background in machine learning. Things are moving so fast its hard to keep up! Look forward to your future videos 👍

AiDeepDive
Автор

Just discovered your channel. Love your explanation. You breakdown the details and explain them in a simple way that anyone interested in this topic can easily understand. Superb. Thanks

LoneRanger.
Автор

Thank you so much! This video was an incredible help to me. Understanding llms was challenging for me, but this video made a significant difference. I'm extremely grateful for the clarity it provided. It truly made a big impact on my understanding.

azemashaik
Автор

Superhuman performance on narrowly defined tasks. Absolutely the direction for business environments. Great video

brandonheaton
Автор

Nice pacing, to-the-point explanations and helpful visuals!

russrussrusstan
Автор

Great overview of fine tuning methods on different llms 👍

henkhbit
Автор

Thank you for the transcription, it's help a lot to understand for non native english with the auto-translation.

HcPlpM
Автор

Awesome! The best overview about this fast changing area of knowledge.

jpchauny
Автор

another fantastic video...so well done.

theshrubberer
Автор

amazing video, I needed to learn this thank you so much

thuraya
Автор

So clear. Thank you so much for this wonderful video!

wcemkfd
Автор

I think that having similar video but that explains different important machine learning terminology or concepts that are associated to the things you talked in this video, would be of great benefit to the community.

mirzacickusic
Автор

Very detailed and clear explanation! Thanks!

gigabytechanz
Автор

What a true learning experience. You simplified this for me 😊

FungaiNdemeraYoutube
Автор

Really nicely done, appreciate the video.

cmthimmaiah
Автор

This is an exceptionally accessible explanation of the Large Language Model evolution. While I have worked with these models through frameworks like AutoGPT and LangChain I did not have a deep understanding. With this now, it seems that I need to learn about training my own model and how to incorporate our own internal information. We have teams of people working and documenting processes on internal Wiki and large markdown notebooks. Getting that data into a model that a new team member could just ask “What is the process to request the hardware purchase of 8x H100 tensors?”
My experience with bringing new people into teams is that many have some level of apprehension about asking questions about standard processes. This could be anything from requesting VPN credentials to long-term financial forecasting. Yeah, I think this could be good for people to help free some intrinsic knowledge locked away in these silos.

JasonFowler
Автор

Very well thought in terms of format and content to explain the whole concept. Thank you very much for this video. Keep it up!!!👌

RachidElBoukiouty
Автор

Excellent! Very informative. Thank you!

romantercero
welcome to shbcf.ru