---
title: FLUX.1-dev-LoRA-Modern_Pixel_art
canonical_url: "https://www.modelscope.cn/models/UmeAiRT/FLUX.1-dev-LoRA-Modern_Pixel_art"
md_url: "https://www.modelscope.cn/models/UmeAiRT/FLUX.1-dev-LoRA-Modern_Pixel_art.md"
repository: UmeAiRT/FLUX.1-dev-LoRA-Modern_Pixel_art
last_updated: 2025-09-04
license: mit
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
base_model:
  - black-forest-labs/FLUX.1-dev
base_model_relation: adapter
parameters: 171.8M
tensor_type:
  - F16
library_name:
  - lora
  - diffusers
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 134
stars: 1
tags:
  - text-to-image
  - lora
  - diffusers
  - "template:sd-lora"
  - flux
  - image-generation
---

# FLUX.1-dev-LoRA-Modern_Pixel_art

> FLUX.1-dev-LoRA-Modern_Pixel_art - UmeAiRT 在 ModelScope 开源的模型。LoRA - Modern pixel art

UmeAiRT/FLUX.1-dev-LoRA-Modern_Pixel_art 是 ModelScope 魔搭社区上的 171.8M 参数text-to-image-synthesis模型，采用 mit 许可，基于 black-forest-labs/FLUX.1-dev 构建。

- **Repository**: UmeAiRT/FLUX.1-dev-LoRA-Modern_Pixel_art
- **License**: mit
- **Tasks**: text-to-image-synthesis
- **Parameters**: 171.8M
- **Base model**: black-forest-labs/FLUX.1-dev
- **Tags**: text-to-image, lora, diffusers, template:sd-lora, flux,  image-generation
- **Downloads**: 134
- **Stars**: 1
- **Last updated**: 2025-09-04

Source: https://www.modelscope.cn/models/UmeAiRT/FLUX.1-dev-LoRA-Modern_Pixel_art

---

# LoRA - Modern pixel art

<Gallery />

## Model description 

Here&#39;s a new LoRA in a much more modern style.

Based on games I&#39;ve personally really enjoyed from the modern 2d pixel art category.

This is the first time I&#39;ve worked with such a large dataset (100), so I&#39;m not sure my settings are optimal.

Don&#39;t hesitate to send me feedback or suggestions!

## Trigger words

You should use `umempart` to trigger the image generation.


## Download model

Weights for this model are available in Safetensors format.

[Download](/UmeAiRT/FLUX.1-dev-LoRA-Modern_Pixel_art/tree/main) them in the Files & versions tab.

## Training parameter

epochs : 20

steps : 2000

lora_rank : 32

optimizer : prodigy

resolution : 1024