Instructions to use nldcr/worx_leafjet-sd2_v.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nldcr/worx_leafjet-sd2_v.2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nldcr/worx_leafjet-sd2_v.2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
worx_leafjet on Stable Diffusion via Dreambooth
model by nldcr
This your the Stable Diffusion model fine-tuned the worx_leafjet concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the instance_prompt: leafjet
You can also train your own concepts and upload them to the library by using this notebook.
And you can run your new concept via diffusers: Colab Notebook for Inference, Spaces with the Public Concepts loaded
Here are the images used for training this concept:

example use
[prompt] a man holding a , high quality
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