Can you clean up this text into the style of an executive summary in bullets?

### Scale down: The Bull Case Fine-Tuning Small (<20B) LLMs

- Fine tuning <20B models give it more mileage — faster iteration speed, other examples Iteration rates are fast. Start with an open source model and fine tune for certain use cases.
    - We are starting to see big these smaller models catch up
    - Fine tuing much less complex
- Large models plateau more — NAME_1 even said so
- Ecosystem will form around the open source one like in stable diffusion vs DALL-E
    - This has already played out in images.
- Right now these things can run on XYZ, there is a clear technical roadmap to improvement
- AI super democratized