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license: apache-2.0
language:
- en
base_model:
- black-forest-labs/FLUX.1-dev
pipeline_tag: text-to-image
tags:
- art
- realism
- lora
---
<h1 align="center">Babes LoRA</h1>
<p align="center">Low-Rank Adapter for Flux. Dev trained on <b>100</b> to <b>170</b> babes images.</p>
---
## Why ?
I have no idea... but it works.
Not only is it good at generating instagram-like images, it's also surprisingly great at realism - leading to better results than most flux realism based LoRA
## Usage
Because of the little amount of data and the training techniques used, it is recommended to use these LoRAs with weights above `1.0`.
At these weights it does not mix very well with other LoRAs.
Weights are provided in `safetensors` format, so they can be used with any generation library or platform.
## Preview
| Preview | Version | Recommended Usage/LoRA Weight |
| --- | --- | --- |
|  | - | _Raw output from Flux Dev_ |
|  | base | min=1.44, max=3.0 |
|  | 1.1 | min=1.44, max=3.0 |
|  | 1.1a | min=2.0, max=2.44 |
|  | 1.1b | min=2.0, max=2.44 |
|  | 1.2a | min=1.44, max=2.0 |
|  | 1.2b | min=1.44, max=3.0 |
|  | 1.3a | min=1.44, max=2.0 |
|  | 1.4a | min=1.44, max=2.0 `Latest dataset` |
|  | 1.5a | min=1.44, max=2.0 `Latest dataset` |
|  | 1.6a | min=1.44, max=2.0 `Latest dataset` |
> [!NOTE]
> 1.5a and 1.6a are using a different LoRA Rank (8 and 16 respectively)
## BibTeX
```bibtex
@Misc{babes,
title = {Babes: Flux Low-Rank Adapter trained on 100 babes images},
author = {Hugo Ventura},
howpublished = {\url{https://huggingface.co/hugovntr/babes}},
year = {2025}
}
```
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