# Replicate — Using synthetic training data to improve Flux finetunes

- Company: Replicate (replicate.com)
- Announced: 2024-09-20T00:00:00+00:00
- Subject: Platform
- Models affected: Flux, consistent-character
- Source: https://replicate.com/blog/using-synthetic-data-to-improve-flux-finetunes
- Record: https://forck.live/items/2513-using-synthetic-training-data-to-improve-flux-finetunes

Replicate's blog post describes three techniques for using synthetic training data to improve Flux fine-tuned models: generating training data from a single image using the consistent-character model, using outputs from the fine-tuned model itself as training data, and combining multiple LoRA styles to diversify training data.

## Evidence

Verbatim from https://replicate.com/blog/using-synthetic-data-to-improve-flux-finetunes:

> In this post I’ll cover some techniques you can use to generate synthetic training data to help improve the accuracy, diversity, and stylistic range of your fine-tuned Flux models.

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Record: https://forck.live/items/2513-using-synthetic-training-data-to-improve-flux-finetunes
Catalogue: https://forck.live/llms.txt
Feed: https://forck.live/feed.md