Instructions to use cicalooo/krea2_unidepth_depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cicalooo/krea2_unidepth_depth 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("cicalooo/krea2_unidepth_depth") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/Screenshot 2026-08-02 005154.png
text: '-'
base_model: krea/Krea-2-Raw
instance_prompt: null
license: mit
krea2_unidepth_depth_exp_v1

- Prompt
- -
Download model
Download them in the Files & versions tab.