Interesting that the underlying model, a LoRA fine-tune of Qwen2.5-Coder-32B, relies on synthetic data from Claude[1]:

  But we had a classic chicken-and-egg problem—we needed data to train the model, but we didn't have any real examples yet. So we started by having Claude generate about 50 synthetic examples that we added to our dataset. We then used that initial fine-tune to ship an early version of Zeta behind a feature flag and started collecting examples from our own team's usage.

  ...

  This approach let us quickly build up a solid dataset of around 400 high-quality examples, which improved the model a lot!

I checked the training set, but couldn't quickly identify which were 'Claude' produced[2]. Would be interesting to see them distinguished out.

[1]: https://zed.dev/blog/edit-prediction [2]: https://huggingface.co/datasets/zed-industries/zeta