k4t-krea / README.md
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---
base_model: krea/Krea-2-Raw
tags:
- text-to-image
- diffusers
- lora
- krea2
- template:sd-lora
license: apache-2.0
instance_prompt: "K4TD woman"
widget:
- text: "A K4TD woman wearing futuristic neon armor, standing in the middle of a rain-slicked cyberpunk street filled with glowing holographic advertisements."
output:
url: sample_0.png
- text: "A K4TD woman in a flowing linen dress, reading an ancient leather-bound book within a sun-drenched Mediterranean garden overgrown with white bougainvillea."
output:
url: sample_1.png
- text: "A K4TD woman as a deep-sea explorer, wearing a high-tech diving suit and swimming alongside bioluminescent jellyfish in a dark, shimmering oceanic abyss."
output:
url: sample_2.png
---
# Krea 2 LoRA — aimalias/k4t
<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 `K4TD woman` to invoke the concept.
## Samples
![sample](./sample_0.png)
> *"A K4TD woman wearing futuristic neon armor, standing in the middle of a rain-slicked cyberpunk street filled with glowing holographic advertisements."*
![sample](./sample_1.png)
> *"A K4TD woman in a flowing linen dress, reading an ancient leather-bound book within a sun-drenched Mediterranean garden overgrown with white bougainvillea."*
![sample](./sample_2.png)
> *"A K4TD woman as a deep-sea explorer, wearing a high-tech diving suit and swimming alongside bioluminescent jellyfish in a dark, shimmering oceanic abyss."*
## 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("aimalias/k4t")
image = pipe("A K4TD woman wearing futuristic neon armor, standing in the middle of a rain-slicked cyberpunk street filled with glowing holographic advertisements.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
```