Instructions to use lamm-mit/stable-diffusion-leaf-V5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lamm-mit/stable-diffusion-leaf-V5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lamm-mit/stable-diffusion-leaf-V5", 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
File size: 982 Bytes
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license: apache-2.0
tags:
- text-to-image
- science
---
### leaf on Stable Diffusion via Dreambooth
#### model by mjbuehler
This a Stable Diffusion model fine-tuned the leaf concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the `instance_prompt`: **<leaf microstructure>**
Here are the images used for training this concept:

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