Instructions to use sdkcompetent/clo3lt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sdkcompetent/clo3lt 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("sdkcompetent/clo3lt") prompt = "A futuristic cyberpunk cityscape at night with neon rain, featuring a clo3lt floating in a glowing holographic display." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Krea 2 LoRA โ sdkcompetent/clo3lt

- Prompt
- A futuristic cyberpunk cityscape at night with neon rain, featuring a clo3lt floating in a glowing holographic display.

- Prompt
- A serene ancient Japanese garden with cherry blossoms falling, where a clo3lt rests on a mossy stone lantern.

- Prompt
- An epic cinematic shot of a deep space nebula, showing a colossal clo3lt drifting past a shimmering supernova.
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 clo3lt to invoke the concept.
Samples
"A futuristic cyberpunk cityscape at night with neon rain, featuring a clo3lt floating in a glowing holographic display."
"A serene ancient Japanese garden with cherry blossoms falling, where a clo3lt rests on a mossy stone lantern."
"An epic cinematic shot of a deep space nebula, showing a colossal clo3lt drifting past a shimmering supernova."
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("sdkcompetent/clo3lt")
image = pipe("A futuristic cyberpunk cityscape at night with neon rain, featuring a clo3lt floating in a glowing holographic display.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
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Model tree for sdkcompetent/clo3lt
Base model
krea/Krea-2-Raw

