README.md

---
base_model: krea/Krea-2-Raw
tags:
- text-to-image
- diffusers
- lora
- krea2
- template:sd-lora
license: apache-2.0
instance_prompt: "Guille"
widget:
- text: "A cinematic shot of Guille as a futuristic cyberpunk detective standing in a rain-slicked neon alleyway, wearing a holographic trench coat."
  output:
    url: sample_0.png
- text: "A whimsical oil painting of Guille as a tiny garden sprite napping inside the petals of a giant, glowing lotus flower."
  output:
    url: sample_1.png
- text: "An epic wide shot of Guille as a majestic astronaut exploring a crystalline desert on a distant purple planet under three moons."
  output:
    url: sample_2.png
---

# Krea 2 LoRA — guillekenzo/guille

<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 `Guille` to invoke the concept.

## Samples

![sample](./sample_0.png)

> *"A cinematic shot of Guille as a futuristic cyberpunk detective standing in a rain-slicked neon alleyway, wearing a holographic trench coat."*

![sample](./sample_1.png)

> *"A whimsical oil painting of Guille as a tiny garden sprite napping inside the petals of a giant, glowing lotus flower."*

![sample](./sample_2.png)

> *"An epic wide shot of Guille as a majestic astronaut exploring a crystalline desert on a distant purple planet under three moons."*

## 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("guillekenzo/guille")
image = pipe("A cinematic shot of Guille as a futuristic cyberpunk detective standing in a rain-slicked neon alleyway, wearing a holographic trench coat.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
```