Create Synthetic Dataset from 1 TOPIC for Instruction Finetuning

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Unlock the power of custom dataset creation using advanced AI models! Create Synthetic Dataset for Instruction Finetuning. In this video, we'll explore how to leverage LLaMA 3.1 and Nemotron 4 to generate synthetic datasets for instruction fine-tuning. Perfect for AI enthusiasts and developers, this tutorial walks you through every step, ensuring you can optimize your models effectively. 🚀✨

In this video, you'll learn:
Introduction to LLaMA 3.1 and Nemotron 4 - Discover the capabilities of these powerful language models.
Generating Subtopics - How to create detailed subtopics from a single topic.
Creating Questions - Techniques to generate comprehensive questions for each subtopic.
Generating Responses - Learn to produce multiple high-quality responses using AI.
Filtering for Quality - Use the Nemotron reward model to ensure response quality.
Uploading to Hugging Face - Step-by-step guide to uploading your dataset.

🔧 Setup Steps:
Install necessary packages: pip install openai datasets
Export your Hugging Face token and Nvidia API key.
Write and run the Python script to generate and filter datasets.
Upload the final dataset to Hugging Face.

🔥 Benefits:
Enhance your model’s instruction fine-tuning with high-quality synthetic data.
Save time and resources by automating dataset creation.
Improve AI performance with robust and diverse training data.

🔗 Links:

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💬 Comment below with any questions or topics you’d like us to cover next.

Timestamps:
0:00 Introduction and Overview
1:13 LLaMA 3.1 & Nemotron 4 Overview
2:26 Step 1: Generating Subtopics
3:53 Step 2: Creating Questions
5:20 Step 3: Generating Responses
6:59 Step 4: Filtering Responses with Reward Model
8:10 Uploading Dataset to Hugging Face
10:05 Final Thoughts and Next Steps

Enjoy the video and happy dataset creation! 🌟

Mervin Praison

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Комментарии

This is awesome. For the next video, I have a suggestion: Suppose I have multiple PDF files containing a lot of information about my organization. How can I use a large language model (LLM) like the one you used above to create a dataset extracted from the knowledge provided in these PDFs?

Menasaat

i also generate synthetic datasets... a secret tip for alignment... set the mood and tone as parameters in the prompt as well to generate the questions as response (make the dataset a little more dynamic)

ByteBop

This is amazing.! Can you also explain how to create a classification model from the generated dataset ?

swetharavishankar

first time to know that LLMs can generate datasets! thank a lot

litttlemooncream

Really great tutorial. Keep em' coming. First time seeing NIMs demo.

maruc

Thank you for this awesome tutorial. I request you to kindly make a video on synthetic dataset generation from pdf files.
Thank you so much

atultiwari

Super cool! Just did something extremely similar but in Google Sheets, so my non-tech peers can help.

grtbigtreehugger

Wow! Great Tutorial Mervin this is what I'm exactly looking for fine tuning. I tested it and it worked perfectly. I have a question, from my understanding from your blog and video, this dataset is suitable for ORPO fine-tuning (AI feedback scores)? Can I still use it for SFT by filtering out the responses (rows) with best scores?

chaithanyavamshi

hey buddy, can't we create the synthetic dataset for images? i mean uploading images and getting responses for the questions... how to do it

kolasatheesh

Can we use ask LLMs to outline, create questions, reply, summerise BOOKS and use that to fine tune LLMs?

vitalis

Bro create a best model for tamil
We don’t have best gpu’s
If you do it we can createit for many usecases

commoncats

I'm still fuzzy about when is creating a synthetic data useful in a practical scenario for me, as a single person, not a large company that needs to fine-tune LLM's. Can someone clarify? What's the real world use for this?

fascinatingfactsabout

Use claude to do this. No model in this world is even close to claude currently. Dont beleive the benchmarks. The difference is huge

TheBestgoku

Create Synthetic Dataset from 1 TOPIC for Instruction Finetuning

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