fine-tuning

🗂️ AI & Agents · View mindmap

title: “Fine-Tuning”

Fine-Tuning

Fine-tuning is the process of adapting a pre-trained machine learning model to perform well on a specific task or dataset by updating its parameters through additional training with new data. This technique leverages existing knowledge in the base model, reducing the need for large amounts of labeled data and enabling more efficient development cycles.

• transfer-learning
• unsloth
• gemma-4-e2b
• rag
• embedding-models

Recent Resources

• Fine-Tune Gemma-4 on Your Own Dataset Locally: Step-by-Step Tutorial

  • Clip title: Fine-Tune Gemma-4 on Your Own Dataset Locally: Step-by-Step Tutorial
  • Author / channel: Fahd Mirza
  • URL: https://www.youtube.com/watch?v=cHpB0PTRx5A
  • Summary: This video provides a practical, step-by-step tutorial on [[concepts/base-model-adaptation|fine-tuning Ge

• Fine-tuning LLMs with Unsloth: Methods, Applications, and Training Pipeline

  • Clip title: How to Fine-tune LLMs with Unsloth: Complete Guide
  • Author / channel: pookie
  • URL: https://www.youtube.com/watch?v=Lt7KrFMcCis
  • Summary: Comprehensive guide covering theoretical underpinnings and practical execution of fine-tuning Large Language Models]] using the unsloth library.