Gemma 2 Fine Tuning for Dummies (with 16k, 32k,... Context) [Full Tutorial]
Learn how to customize the open-source Gemma 2 AI model for your specific needs using Unsloth and Hugging Face. This step-by-step tutorial covers:
Setting up Google Colab with GPU acceleration
Preparing your dataset for fine-tuning
Configuring the model (including 9B vs 27B selection)
Training process and memory management
Testing your fine-tuned model
Saving and uploading to Hugging Face
Perfect for developers and AI enthusiasts looking to create tailored language models. No prior experience required.
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Demonstration Diagram and Code: https://github.com/nodematiclabs/gemm...
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0:00 Conceptual Overview
2:21 GPU/TPU Selection (Runtime)
3:19 Unsloth/Huggingface Installs
4:00 4-Bit Quantized Gemma 2
4:44 Token Counts
8:00 Fine-Tuning Configuration
8:32 LoRA (QLoRA) Adapters
9:38 Dataset Creation
12:55 Model Training
14:57 Out of Memory Errors
17:30 Inference and Testing
20:47 Hugging Face Upload
#gemma #machinelearning #huggingface #finetuning