cecell/micropython-lora

Each .jsonl file contains a list of prompt-response pairs, one per line.

If you're using this as a base for your own fine-tuning:

1. Clone the repo
2. Select or customize subcategories
3. Feed .jsonl files into your LoRA training pipeline (e.g., peft, Axolotl, QLoRA)
4. Validate results with your model using structured tests or interactive review

• Include test coverage datasets (e.g., expected model completions)
• Add platform-specific code distinctions (e.g., ESP32 vs. Raspberry Pi Pico)
• Link to model outputs and benchmarks for comparison

🙌 Contributions This is starting as a personal project, but it would be cool if this became a public endeavor. I'd love for the effort to help more than just myself.

I welcome pull requests to improve this repo. I only ask for your patience as I'm still learning — at this time, ChatGPT gets a lot of credit as the brains behind this operation!