We don't sell fine-tuning tools - we're an open tool for finding the best way of running your AI workload. We support evaluating/comparing a variety of methods: prompting, prompt generators (few shot, repairs), various models, and fine-tuning from 5 different providers.
The focus of the tool is that it lets you try them all, side by side, and easily evaluate the results. Fine-tuning is one tool in a tool chest, which often wins, but not always. You should use evals to pick the best option for you. This also sets you up to iterate (when you find bugs, want to change the product, or new models comes out).
Re:demo -- would you want a demo or detailed evals and open datasets (honest question)? Single-shot examples are hard to compare, but the benefits usually come out in evals at scale. I'm definitely open to making this. Open for suggestions on what would be the most helpful (format and use case).
It's all on Github and free: https://github.com/kiln-ai/kiln
The focus of the tool is that it lets you try them all, side by side, and easily evaluate the results. Fine-tuning is one tool in a tool chest, which often wins, but not always. You should use evals to pick the best option for you. This also sets you up to iterate (when you find bugs, want to change the product, or new models comes out).
Re:demo -- would you want a demo or detailed evals and open datasets (honest question)? Single-shot examples are hard to compare, but the benefits usually come out in evals at scale. I'm definitely open to making this. Open for suggestions on what would be the most helpful (format and use case).
It's all on Github and free: https://github.com/kiln-ai/kiln