Instructions to use 0xahzam/biodiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 0xahzam/biodiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("0xahzam/biodiffusion", 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
BioDiffusion Model ๐พ
Exploring the intersection of art and biology by fine-tuning diffusion models on datasets like david goodsell's work to generate sci-art that is unique but also really fascinating.
note: don't forget to add in the style of DavidGoodsell in the prompt
Some eye-blessing generated examples :)
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