README.md

---
base_model: krea/Krea-2-Raw
tags:
- text-to-image
- diffusers
- lora
- krea2
- template:sd-lora
license: apache-2.0
instance_prompt: "e6gz"
widget:
- text: "A majestic snow leopard leaping across a jagged Himalayan cliffside during a swirling blizzard, captured in hyper-realistic detail e6gz"
  output:
    url: sample_0.png
- text: "A sleek, neon-lit cyberpunk motorcycle speeding down a rain-slicked Tokyo street at midnight with vibrant light trails e6gz"
  output:
    url: sample_1.png
- text: "An elderly clockmaker meticulously repairing a golden pocket watch inside a dusty, sun-drenched Victorian workshop e6gz"
  output:
    url: sample_2.png
---

# Krea 2 LoRA — Eggsbena/eggs

<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 phrase `e6gz` to invoke the concept.

## Samples

![sample](./sample_0.png)

> *"A majestic snow leopard leaping across a jagged Himalayan cliffside during a swirling blizzard, captured in hyper-realistic detail e6gz"*

![sample](./sample_1.png)

> *"A sleek, neon-lit cyberpunk motorcycle speeding down a rain-slicked Tokyo street at midnight with vibrant light trails e6gz"*

![sample](./sample_2.png)

> *"An elderly clockmaker meticulously repairing a golden pocket watch inside a dusty, sun-drenched Victorian workshop e6gz"*

## 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("Eggsbena/eggs")
image = pipe("A majestic snow leopard leaping across a jagged Himalayan cliffside during a swirling blizzard, captured in hyper-realistic detail e6gz", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
```