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Introduction and Overview
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LLaMA 3.1 & Nemotron 4 Overview
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Step 1: Generating Subtopics
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Step 2: Creating Questions
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Step 3: Generating Responses
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Step 4: Filtering Responses with Reward Model
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Uploading Dataset to Hugging Face
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Final Thoughts and Next Steps
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Learn how to create synthetic datasets for instruction fine-tuning using LLaMA 3.1 and Nemotron 4 in this comprehensive tutorial video. Discover techniques for generating subtopics, creating questions, producing high-quality responses, and filtering content using AI models. Follow step-by-step instructions to set up the necessary tools, write and run Python scripts, and upload your custom dataset to Hugging Face. Gain insights into enhancing AI model performance with diverse training data and automating the dataset creation process. Perfect for AI developers and enthusiasts looking to optimize their models effectively.

Creating Synthetic Datasets for Instruction Finetuning with LLaMA and Nemotron

Mervin Praison
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