---
base_model: krea/Krea-2-Raw
tags:
- text-to-image
- diffusers
- lora
- krea2
- template:sd-lora
license: apache-2.0
instance_prompt: "EC4M woman"
widget:
- text: "A cinematic shot of an EC4M woman wearing bioluminescent armor, standing amidst a floating neon jungle on a distant alien planet."
  output:
    url: sample_0.png
- text: "A nostalgic 1950s oil painting of an EC4M woman reading a leather-bound book in a cozy, sun-drenched library filled with dust motes."
  output:
    url: sample_1.png
- text: "A high-fashion editorial photo of an EC4M woman draped in iridescent silk, posing against the stark, brutalist concrete architecture of a futuristic city."
  output:
    url: sample_2.png
---

# Krea 2 LoRA — aimalias/ec4m

<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 `EC4M woman` to invoke the concept.

## Samples

![sample](./sample_0.png)

> *"A cinematic shot of an EC4M woman wearing bioluminescent armor, standing amidst a floating neon jungle on a distant alien planet."*

![sample](./sample_1.png)

> *"A nostalgic 1950s oil painting of an EC4M woman reading a leather-bound book in a cozy, sun-drenched library filled with dust motes."*

![sample](./sample_2.png)

> *"A high-fashion editorial photo of an EC4M woman draped in iridescent silk, posing against the stark, brutalist concrete architecture of a futuristic city."*

## 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/ec4m")
image = pipe("A cinematic shot of an EC4M woman wearing bioluminescent armor, standing amidst a floating neon jungle on a distant alien planet.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
```