---
base_model: krea/Krea-2-Raw
tags:
- text-to-image
- diffusers
- lora
- krea2
- template:sd-lora
license: apache-2.0
instance_prompt: "score_4"
widget:
- text: "A futuristic cyborg samurai standing in the middle of a neon-drenched Tokyo street during a rainstorm, cinematic lighting, score_4."
  output:
    url: sample_0.png
- text: "A whimsical miniature village built inside a giant hollowed-out pumpkin, soft golden hour sunlight filtering through the walls, score_4."
  output:
    url: sample_1.png
- text: "An ancient stone temple floating amidst a sea of swirling cosmic nebulae and sparkling stardust, ethereal atmosphere, score_4."
  output:
    url: sample_2.png
---

# Krea 2 LoRA — TensorVizion/VexKrea

<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 `score_4` to invoke the concept.

## Samples

![sample](./sample_0.png)

> *"A futuristic cyborg samurai standing in the middle of a neon-drenched Tokyo street during a rainstorm, cinematic lighting, score_4."*

![sample](./sample_1.png)

> *"A whimsical miniature village built inside a giant hollowed-out pumpkin, soft golden hour sunlight filtering through the walls, score_4."*

![sample](./sample_2.png)

> *"An ancient stone temple floating amidst a sea of swirling cosmic nebulae and sparkling stardust, ethereal atmosphere, score_4."*

## 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("TensorVizion/toucanflux")
image = pipe("A futuristic cyborg samurai standing in the middle of a neon-drenched Tokyo street during a rainstorm, cinematic lighting, score_4.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
```