metadata
base_model: krea/Krea-2-Raw
tags:
- text-to-image
- diffusers
- lora
- krea2
- template:sd-lora
license: apache-2.0
instance_prompt: p0ar4
widget:
- text: >-
A futuristic cyberpunk city street drenched in neon rain, featuring a
holographic p0ar4 floating above a crowded marketplace.
output:
url: sample_0.png
- text: >-
A serene, sun-drenched Tuscan vineyard where a rustic wooden table holds a
crystal vase and a single p0ar4.
output:
url: sample_1.png
- text: >-
An epic underwater kingdom with iridescent coral towers and a glowing
p0ar4 drifting through a school of shimmering fish.
output:
url: sample_2.png
Krea 2 LoRA — saik0s/p0ar4
- Prompt
- A futuristic cyberpunk city street drenched in neon rain, featuring a holographic p0ar4 floating above a crowded marketplace.
- Prompt
- A serene, sun-drenched Tuscan vineyard where a rustic wooden table holds a crystal vase and a single p0ar4.
- Prompt
- An epic underwater kingdom with iridescent coral towers and a glowing p0ar4 drifting through a school of shimmering fish.
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 p0ar4 to invoke the concept.
Samples
"A futuristic cyberpunk city street drenched in neon rain, featuring a holographic p0ar4 floating above a crowded marketplace."
"A serene, sun-drenched Tuscan vineyard where a rustic wooden table holds a crystal vase and a single p0ar4."
"An epic underwater kingdom with iridescent coral towers and a glowing p0ar4 drifting through a school of shimmering fish."
Use it with diffusers
import torch
from diffusers import Krea2Pipeline
pipe = Krea2Pipeline.from_pretrained("krea/Krea-2-Turbo", torch_dtype=torch.bfloat16).to("cuda")
pipe.load_lora_weights("saik0s/p0ar4")
image = pipe("A futuristic cyberpunk city street drenched in neon rain, featuring a holographic p0ar4 floating above a crowded marketplace.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")