Watch End-to-End (small) LLM Fine-tuning Tutorial (from data to model to live demo) | On DGX Spark Video Tutorial


Tutorial Details & Info

Tutorial Title: End-to-End (small) LLM Fine-tuning Tutorial (from data to model to live demo) | On DGX Spark
Instructor / Channel: Daniel Bourke
Lesson Runtime: 59:49 Minutes
Publish Date: January 09, 2026
Total Students / Views: 90,182 views

Master the concepts in End-to-End (small) LLM Fine-tuning Tutorial (from data to model to live demo) | On DGX Spark created by Daniel Bourke. The total lesson runtime is 59:49 minutes with crystal clear HD video and audio quality. Watch this video tutorial for free without any subscription or sign-up required.

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Course Description & Lesson Notes

Official Video Description:

In this video we fully fine-tune Google's Gemma 3 270M Small Language Model to do structured data extraction. Because the Gemma 3 270M is quite small in world of LLMs, we're able to do all of the training locally on a NVIDIA DGX Spark (see here for more: https://nvda.ws/4iQXZU4). The code should also run in Google Colab. If you have any issues, please let me know in a comment. Links: Google Colab Notebook - https://colab.research.google.com/drive/1hV6Gcz8vBRS9t0bYkBp6W1ne_yqG6mJx?usp=sharing Learn Hugging Face Book Version - https://www.learnhuggingface.com/notebooks/hugging_face_llm_full_fine_tune_tutorial Dataset - https://huggingface.co/datasets/mrdbourke/FoodExtract-1k Base model (Gemma 3 270M) - https://huggingface.co/google/gemma-3-270m-it Demo - https://huggingface.co/spaces/mrdbourke/FoodExtract-v1 Past livestreams (where we coded the notebook from scratch): Part 1 (loading the model and fine-tuning it) - https://youtube.com/live/M32fJdG3D_A?feature=share Part 2 (sharing our model and creating a demo) - https://youtube.com/live/zt8t-xT26rA?feature=share Courses I teach: Learn AI/ML (beginner-friendly course) - https://dbourke.link/ZTMMLcourse Learn Hugging Face - https://dbourke.link/ZTMHuggingFace Learn TensorFlow - https://dbourke.link/ZTMTFcourse Learn PyTorch - https://dbourke.link/ZTMPyTorch Connect elsewhere: Download Nutrify (my startup) - https://apple.co/4ahM7Wc My website - https://www.mrdbourke.com X/Twitter - https://www.twitter.com/mrdbourke LinkedIn - www.linkedin.com/in/mrdbourke Get email updates on my work - https://dbourke.link/newsletter Read my novel Charlie Walks - https://www.charliewalks.com Timestamps: 00:00 Welcome to the Machine Learning Cooking Show 00:57 Why Fine-Tune Your Own Model? 02:47 Ingredients and Preparation 05:45 Understanding the Task and Data 18:27 Formatting Data for the Model 20:41 Testing the Base Model 30:29 Model Fine-Tuning 31:08 Testing the Model with Sample Data 32:26 Setting Up Supervised Fine-Tuning 34:42 Training the Model Locally 36:38 Evaluating Model Performance 42:55 Uploading the Model to Hugging Face Hub 47:02 Creating a Demo with Gradio 56:08 Speeding Up Inference with Batch Processing 58:11 Next Steps and Conclusion

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Learn how to apply End-to-End (small) LLM Fine-tuning Tutorial (from Data To Model To Live Demo) | On DGX Spark with this in-depth video tutorial guide. Throughout this course, you will learn essential skills for End-to-End (small) LLM Fine-tuning Tutorial (from Data To Model To Live Demo) | On DGX Spark.

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🎓 Lesson Overview & Learning Outcomes:

Welcome to the step-by-step video guide for End-to-End (small) LLM Fine-tuning Tutorial (from data to model to live demo) | On DGX Spark taught by Daniel Bourke. This tutorial provides a comprehensive walkthrough designed to take you from foundational principles to practical implementation.

💡 Key Topics Covered in This Course:

  • Core Fundamentals & Setup: Understanding the workspace, essential tools, and initial setup for End-to-End (small) LLM Fine-tuning Tutorial (from data to model to live demo) | On DGX Spark.
  • Step-by-Step Practical Demonstration: Hands-on implementation guided by Daniel Bourke with real-world examples.
  • Best Practices & Key Shortcuts: Time-saving workflows, keyboard shortcuts, and industry-standard recommendations.
  • Troubleshooting & Common Pitfalls: How to avoid common beginner errors and optimize your workflow for peak efficiency.

📋 Recommended Prerequisites & Study Notes:

No prior advanced experience is required. Follow along with the video player above on any desktop computer, tablet, or mobile device. Pause and rewind at key steps to practice along with the instructor.

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