Explore the capabilities of Meta AI's Llama 3.2 (3B) model in this comprehensive tutorial video. Learn how to set up and run the model using Ollama, and dive into practical applications such as data labeling, text summarization, structured data extraction, and question-answering. Follow along with Jupyter Notebook demonstrations and discover how to leverage this local language model for various natural language processing tasks. Gain insights into the model's performance and potential use cases, from creating LinkedIn posts to extracting information from tables. Perfect for developers and AI enthusiasts looking to harness the power of edge-optimized language models.
Local Llama 3.2 (3B) Tutorial - Summarization, Structured Text Extraction, and Data Labelling
Overview
Syllabus
- Welcome
- Text tutorial on MLExpert.io
- Llama 3.2 on Ollama
- Download and run Llama 3.2 3B
- Jupyter Notebook setup
- Coding
- Labelling data
- Text summarization
- LinkedIn post
- Structured data extraction
- Rag/Question-answering
- Table data extraction
- Conclusion
Taught by
Venelin Valkov
