Instructions to use Nanico/evb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Nanico/evb 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("Nanico/evb") prompt = "A futuristic cyberpunk city street drenched in neon rain, featuring a floating mechanical cat evb with glowing circuitry." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Krea 2 LoRA โ Nanico/evb

- Prompt
- A futuristic cyberpunk city street drenched in neon rain, featuring a floating mechanical cat evb with glowing circuitry.

- Prompt
- An ancient, overgrown jungle temple where a majestic stone golem evb rests under a canopy of bioluminescent ferns.

- Prompt
- A minimalist high-fashion studio shot of a sleek, iridescent porcelain sculpture evb set against a stark matte black background.
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 evb to invoke the concept.
Samples
"A futuristic cyberpunk city street drenched in neon rain, featuring a floating mechanical cat evb with glowing circuitry."
"An ancient, overgrown jungle temple where a majestic stone golem evb rests under a canopy of bioluminescent ferns."
"A minimalist high-fashion studio shot of a sleek, iridescent porcelain sculpture evb set against a stark matte black background."
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("Nanico/evb")
image = pipe("A futuristic cyberpunk city street drenched in neon rain, featuring a floating mechanical cat evb with glowing circuitry.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
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Model tree for Nanico/evb
Base model
krea/Krea-2-Raw

