Anyone can Fine Tune LLMs using LLaMA Factory: End-to-End Tutorial

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Welcome to an exciting journey where I guide you through the world of Large Language Model Fine-Tuning using the incredible 'LLaMA-Factory'! This tutorial is tailored for anyone eager to delve into the realm of Generative AI without getting bogged down by complex coding.

LLaMA-Factory stands out as a user-friendly fine-tuning framework that supports a variety of language models including LLaMA, BLOOM, Mistral, Baichuan, Qwen, and ChatGLM. What makes this tool remarkable is its simplicity and effectiveness, allowing you to learn and fine-tune language models with just a few clicks.

In this video, I demonstrate how effortlessly you can fine-tune these models using a no-code tool within Google Colab Pro, leveraging powerful GPUs like the V100 or A100. Whether you're a beginner or an experienced enthusiast in Generative AI, this tutorial will unlock new potentials in your language model projects.

Key Highlights:

1. Introduction to LLaMA-Factory and its capabilities
2. Step-by-step guide on fine-tuning different language models
3. Tips for optimizing performance with Google Colab Pro's GPUs
4. Practical examples to get you started immediately

Remember, the world of Generative AI is vast, and with tools like LLaMA-Factory, it's more accessible than ever. So, if you find this tutorial helpful, please hit the 'Like' button, share it with your friends, and subscribe to the channel for more content on Generative AI and language model fine-tuning. Your support helps me create more helpful content like this.

Let's dive into the world of easy and powerful language model fine-tuning together!

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I just able to fine tune to build my own SQLGPT... Thank you so much sir 🙏

iuidehx

00:05 LLAMA Factory makes fine-tuning large language models accessible to anyone.
02:23 Llama Factory provides a framework for fine-tuning LLMs on various datasets and models.
06:42 LLAMA Factory can be set up locally or on the public cloud as per your requirement.
08:48 Importance of understanding large language models and the need for sustainable growth in your career
12:59 Defining prompt, query, and response for fine-tuning LLMs
15:19 Using LLaMA Factory for fine tuning LLMs
19:33 Advanced configuration and quantization are crucial for model loading and performance.
21:30 Adjusting the LLM pre-training parameters for compute constraints.
25:29 Fine-tuning LLMs using LLaMA Factory: Model weight download and training process
27:13 Model is generalizing well and not overfitting.
30:57 Fine-tuning LLMs with LLaMA Factory for Docker related queries
32:49 LLMs can be fine-tuned easily with personalization options

sailakkshmi

amazing content. thank you for sharing your knowledge. cybersecurity engineer here but im super intrigued by LLMs. im going to try to finetune a chat model on my own proprietary data next

AOSRoyal

very cool stuff. I didn't realize how deep the hugging face web site was. I just did a fine tune with openai and creating my own dataset was time intensive. Now I'll look at HF to see if someone has made a dataset. I'd love to see a video on building a docker container to host an LLM and how to do some basic things with a model loaded in a Docker. One thing is, how would you store all user input/model output to automate the generation of new training data once your app is in production and you need to monitor its performance in real-time.

EmilioGagliardi

Thank you for the great work! Keep up creating these useful and concise videos.

RaghavendraK

Waoow, el internet de las cosas le van a agradecer porque muchas cosas se van a automatizar sin mucho codigo. Gracias.

FredyGonzales

One fine-tuning question NO ONE has been able to explain to me bhai -
How does one go about fine-tuning when the source is a non-fiction book? It needs to be ‘fine-tuning’ specifically. So then, what kind of data preparation I need to do with the book contents (TEXT file). Thoda detail mein explanation mil jaaye toh samajh aaye. Thank you 🙏🏼

LoneRanger.

Interest jagaa diyaa aapne LLMs mein. Dhanyawaad:)

soulfuljourney

I think you are the best youtuber out there, could you male a course for newbies about all of this, cause we got a lot of confussion about AI, deep learning, machine learning, LLM, LMM, LLMs, fine tunning, models, datasets, parameters, tokens etc... Nobody did a course from SCRATCH EXPLAINING all this concepts, could you make one or how can I learn all of this? Some courses or resources for non technical people, I just want to understand all of this and how can I insert my data and make a better AI for my things or some other things.. I dont't understand what is the BEST AI for generate code, why some understand spanish and others dont etc etc

chemaalonso

best video about LLaMA Factory in youtube, but please show how to save the model and push to hugging face with this LLaMa factory .
Thank you.

animeshdas

hey, can you help us by making a video about how do you learn all these new concepts, what are those fundamentals or pre-requisite that you have learned which helps you in learning these things very easily?

FinComInvestNegoSaleStart

Hi, I became your subscriber today :), Nice work indeed ..Can you please help which video you have shown, " How to create your own dataset for fine tuning"

rudrachand

Great video and efforts. Question. If I had a dataset that has questions only not question-answer pair. Is it possible to make the llm iterate over the questions in the dataset and generate responses for these questions?

Mr.AIFella

I liked the video just because you like Manchester United!!!

ihaveacutenose

I can't get llama 2 to work, or llama 3 for that matter, and every single tutorial video I've seen for Llama Factory isn't using a llama model at all : /

HuemanInstrumentality

Very nice and informatic tutorial of fine tuning. I have one question that what is the difference between agents and fine tuning ?As in both cases we are loading our local dataset and from there we can do the chat.

souravbarua

very good, videos, but i ma getting issue on implementing imbedings with greater sequence length like Jina ai , if there is aw y ican use it hlep it has 8k tokesn, i was implementing RAG a asked longer question and it say max token or sequcnce maybe i was using BGE large imbedding wich has 512 sequence and Qdrant, thank you

Cedric_

Please also show how to push and access the finetuned model on huggingface

prathamshah

it will be great to see how you do it with pdf.. do you clean first the pdf.. or will LamaFactory will take care of that?

fabsync

@AIAnytime we have trained the model, but how we can serve the trained custom LLM model as api end-point

ewlgthh

Anyone can Fine Tune LLMs using LLaMA Factory: End-to-End Tutorial

Anyone can Fine Tune LLMs using LLaMA Factory: End-to-End Tutorial

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