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
LUCID

- Prompt
- Screenshot
Model description
https://cdn-uploads.huggingface.co/production/uploads/690e93c2ae6f634188d1d6dd/B_XzIzgcTY23Rp6AnGnrM.mp4
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Model tree for odenroberts/LUCID
Base model
NucleusAI/Nucleus-Image