# Training Design for Text-to-Image Models: Lessons from Ablations

DevFeed: [Training Design for Text-to-Image Models: Lessons from Ablations](<https://devfeed.tech/articles/training-design-for-text-to-image-models-lessons-from-ablations-7035.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/Photoroom/prx-part2>)

Author: David Bertoin; Roman Frigg; Jon Almazán

Published: 2026-02-03T11:25:53Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [text-to-image](<https://devfeed.tech/topics/text-to-image.md>), [foundation-models](<https://devfeed.tech/topics/foundation-models.md>), [Optimization](<https://devfeed.tech/topics/optimization.md>)

Tags: [efficiency](<https://devfeed.tech/tags/efficiency.md>), [experiments](<https://devfeed.tech/tags/experiments.md>), [models](<https://devfeed.tech/tags/models.md>), [open](<https://devfeed.tech/tags/open.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [scale](<https://devfeed.tech/tags/scale.md>), [series](<https://devfeed.tech/tags/series.md>), [techniques](<https://devfeed.tech/tags/techniques.md>), [text-to-image](<https://devfeed.tech/tags/text-to-image.md>), [training](<https://devfeed.tech/tags/training.md>)

## AI overview

This second article in a series documents experiments for training efficient text-to-image foundation models from scratch. Using PRX as the case study, it examines techniques that improve training speed, convergence reliability, and learned representations, comparing them through controlled experiments and combinations against a clean Flow Matching baseline.

## Source excerpt

Welcome back! This is the second part of our series on training efficient text-to-image models from scratch. In the first post of this series, we introduced our goal: training a competitive text-to-image foundation model entirely from scratch, in the open, and at scale. We focused primarily on architectural choices and motivated the core design decisions behind our model PRX.