Summary
This video introduces Large Language Models (LLMs) and explains how they can assist in tasks such as writing blog posts and scripts. It delves into the process of fine-tuning LLMs, which involves teaching the AI to perform specific tasks through examples and detailed information. The video provides a detailed guide on how to fine-tune LLMs, including preparing training data sets, using tools like Nebus, and selecting model sizes based on tasks and associated costs. It concludes with insights on using fine-tuned models for tasks like generating tweets and encourages staying updated on AI tools for continued improvements.
Introduction to LLMs
Introduction to Large Language Models (LLMs) and how they can make tasks like writing blog posts, articles, and scripts easier but still require review time.
Fine-Tuning Explanation
Explanation of fine-tuning, the process of teaching an AI to perform specific tasks by providing examples and detailed information.
Fine-Tuning Process
Detailed guide on how to fine-tune large language models with examples and comparisons of different models for various tasks.
Training Data Set Preparation
Demonstration of preparing a training data set by downloading transcripts, converting them to JSON format, and uploading them for training.
Nebus Fine-Tuning
Explanation and demonstration of using Nebus for fine-tuning models, including uploading training and validation data sets and selecting deployment options.
Model Selection and Cost
Discussion on choosing model sizes based on the task and associated costs for training large language models.
Testing and Deployment
Testing and deploying the fine-tuned model for specific tasks like generating tweets in a desired style.
Conclusion and Recommendations
Final thoughts on the fine-tuning process, the ease of making AI sound like the user, and suggestions for staying updated on AI tools.
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