Instructions to use stablediffusionapi/bdicon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/bdicon with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/bdicon", dtype=torch.bfloat16, device_map="cuda") prompt = "a girl wandering through the forest" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c51652364376e8f38d5242e7cb649c1cbf93bf1e81af487b45a32dd1b8f8dff0
- Size of remote file:
- 246 MB
- SHA256:
- 9353d9ef88d7418ccc534c3268d8535ad981e430733bb78e6052dfb69ce180d0
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