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", torch_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:
- 01812c0aa2f36aa10f39933603354fea737e1e97091714ccca30c7b2cecededa
- Size of remote file:
- 1.72 GB
- SHA256:
- cce4ed46a7b20bc2727ac43be4adab80754152d64a8f853e646c83c841f7a9d8
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