Relabeling Data
Use powerful models to generate new outputs for your data before training.
After importing rows from request logs or uploading a JSONL file, you can optionally relabel each row by sending its messages, tools, and other input parameters to a more powerful model, which will generate an output to replace your row’s existing output. If time or cost constraints prevent you from using the most powerful model available in production, relabeling offers an opportunity to optimize the quality of your training data before kicking off a job.
We provide a number of built-in relabeling options.
Anthropic:
claude-3-opus-20240229
claude-sonnet-3-7-20250219
claude-sonnet-3-5-20241022
OpenAI:
gpt-4-5-preview-02-27
o1-2024-12-17
o3-mini-2025-01-31
gpt-4o-2024-08-06
gpt-4o-2024-11-20
gpt-4-turbo-2024-04-09
gpt-4-0125-preview
gpt-4-1106-preview
gpt-4-0613
Gemini:
gemini-2-0-flash
gemini-2-0-pro-exp-02-05
Meta:
meta-llama-3-1-405b-instruct
DeepSeek:
deepseek-v3
deepseek-r1
Mixture of Agents:
moa-gpt-4o-v1
(Mixture of Agents)moa-gpt-4-turbo-v1
(Mixture of Agents)moa-gpt-4-v1
(Mixture of Agents)
To learn more about Mixture of Agents, a powerful technique for optimizing quality at the cost of speed and price, on the Mixture of Agents page.