Instructions to use Dzoordan/lorry with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Dzoordan/lorry with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Dzoordan/lorry") prompt = "A futuristic neon-lit cyberpunk city street where a sleek, chrome Lorry floats silently above a rain-slicked asphalt road." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Krea 2 LoRA โ Dzoordan/lorry

- Prompt
- A futuristic neon-lit cyberpunk city street where a sleek, chrome Lorry floats silently above a rain-slicked asphalt road.

- Prompt
- A whimsical oil painting of a miniature Lorry made of gingerbread and frosting, parked in a candy-cane forest.

- Prompt
- A cinematic wide shot of a rusted, overgrown Lorry reclaimed by nature in a sun-drenched post-apocalyptic jungle.
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 Lorry to invoke the concept.
Samples
"A futuristic neon-lit cyberpunk city street where a sleek, chrome Lorry floats silently above a rain-slicked asphalt road."
"A whimsical oil painting of a miniature Lorry made of gingerbread and frosting, parked in a candy-cane forest."
"A cinematic wide shot of a rusted, overgrown Lorry reclaimed by nature in a sun-drenched post-apocalyptic jungle."
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("Dzoordan/lorry")
image = pipe("A futuristic neon-lit cyberpunk city street where a sleek, chrome Lorry floats silently above a rain-slicked asphalt road.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
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Model tree for Dzoordan/lorry
Base model
krea/Krea-2-Raw

