Gemma 3 Local Test with Ollama: Coding, Data Extraction, Data Labelling, Summarization, RAG

Gemma 3 is a family of multimodal models from Google Deepmind that comes in 4 different sizes (1B, 4B, 12B and 27B). It is multilingual, supports 128k context window with tool calling and structured output training. We'll take it for a test in a local setup with Ollama, and find if it is any good. Gemma 3 blog post: https://blog.google/technology/developers/gemma-3/ Gemma 3 technical report: https://storage.googleapis.com/deepmind-media/gemma/Gemma3Report.pdf Ollama model: https://ollama.com/library/gemma3:12b AI Bootcamp: https://www.mlexpert.io/ LinkedIn: https://www.linkedin.com/in/venelin-valkov/ Follow me on X: https://twitter.com/venelin_valkov Discord: https://discord.gg/UaNPxVD6tv Subscribe: http://bit.ly/venelin-subscribe GitHub repository: https://github.com/curiousily/AI-Bootcamp 👍 Don't Forget to Like, Comment, and Subscribe for More Tutorials! 00:00 - Gemma 3 overview 03:30 - Ollama model 03:42 - Notebook setup 04:53 - Hip Hop lyrics 06:06 - Coding 09:26 - Data labeling 11:10 - Text summarization 12:30 - LinkedIn post 13:56 - Structured data extraction (with vision test) 17:06 - RAG/Question-answering 18:52 - Table data extraction 19:42 - Conclusion Join this channel to get access to the perks and support my work: https://www.youtube.com/channel/UCoW_WzQNJVAjxo4osNAxd_g/join #gemma #ollama #python #chatgpt #artificialintelligence #llama