Fine-Tuning TinyLLaMA & TinyDolphin for RaspberryPi with Ollama - Ultimate Guide running on Colab

Learn how to fine-tune the TinyLLaMA and TinyDolphin models to run seamlessly on a Raspberry Pi using Ollama!
In this step-by-step tutorial, we’ll guide you through the fine-tuning process, even running on a Google Colab. Then, we go quickly how to set up a yaml file to run with Ollama on your Raspberry Pi.
Whether you're an AI enthusiast or a Raspberry Pi hobbyist, this guide is perfect for anyone looking to explore AI on edge devices. We'll also cover tips and tricks for optimizing performance on limited hardware, ensuring smooth and efficient AI operations.
Original paper about TinyLlama: arxiv.org/abs/...
First part of the tutorial about running Ollama with LLM on RaspberryPi: • How to Run a Local LLM...
Colab with full code: colab.research...
HugginFace repo for TinyDolphin: huggingface.co...
Folder structure and Yaml for launching Ollama with the training model:
/path/to/ollama/models/mytinydolphin/
├── config.json
├── tokenizer.json
├── model.bin
└── other necessary files
name: mytinydolphin
base: mytinydolphin-base
model_files:
- model.bin
tokenizer_files:
- tokenizer.json
parameters:
max_length: 512
temperature: 0.7
How to set up TinyLLaMA & TinyDolphin on a Raspberry Pi
Fine-tuning models using Ollama
Best practices for running AI on limited hardware
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