Instructions to use odenroberts/LUCID with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use odenroberts/LUCID with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("NucleusAI/Nucleus-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("odenroberts/LUCID") prompt = "Screenshot" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/Screenshot 2026-04-21 at 2.22.17 PM.png
text: Screenshot
base_model: NucleusAI/Nucleus-Image
instance_prompt: null
license: unknown
LUCID

- Prompt
- Screenshot
Model description
https://cdn-uploads.huggingface.co/production/uploads/690e93c2ae6f634188d1d6dd/B_XzIzgcTY23Rp6AnGnrM.mp4
Download model
Download them in the Files & versions tab.