---
base_model: krea/Krea-2-Raw
tags:
- text-to-image
- diffusers
- lora
- krea2
- template:sd-lora
license: apache-2.0
instance_prompt: "zmabruma"
widget:
- text: "A futuristic cyberpunk cityscape at midnight where a translucent holographic jellyfish floats above neon skyscrapers, zmabruma, cinematic lighting, 8k resolution."
  output:
    url: sample_0.png
- text: "An ancient, overgrown stone temple deep in a misty rainforest with sunlight filtering through giant ferns, zmabruma, hyper-realistic nature photography."
  output:
    url: sample_1.png
- text: "A surrealist dreamscape featuring floating islands of melting gold and violet clouds under a triple moon sky, zmabruma, digital art masterpiece."
  output:
    url: sample_2.png
---

# Krea 2 LoRA — memo360/mabruma

<Gallery />

A DreamBooth-LoRA for **Krea 2**, trained on **Krea 2 RAW** and shown on **Krea 2 Turbo**. The samples below were generated with this LoRA on Turbo (8 steps).

## Trigger

Use the token `zmabruma` to invoke the concept.

## Samples

![sample](./sample_0.png)

> *"A futuristic cyberpunk cityscape at midnight where a translucent holographic jellyfish floats above neon skyscrapers, zmabruma, cinematic lighting, 8k resolution."*

![sample](./sample_1.png)

> *"An ancient, overgrown stone temple deep in a misty rainforest with sunlight filtering through giant ferns, zmabruma, hyper-realistic nature photography."*

![sample](./sample_2.png)

> *"A surrealist dreamscape featuring floating islands of melting gold and violet clouds under a triple moon sky, zmabruma, digital art masterpiece."*

## Use it with diffusers

```py
import torch
from diffusers import Krea2Pipeline

pipe = Krea2Pipeline.from_pretrained("krea/Krea-2-Turbo", torch_dtype=torch.bfloat16).to("cuda")
pipe.load_lora_weights("memo360/mabruma")
image = pipe("A futuristic cyberpunk cityscape at midnight where a translucent holographic jellyfish floats above neon skyscrapers, zmabruma, cinematic lighting, 8k resolution.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
```