Instructions to use 360ZhiNao/BDM1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 360ZhiNao/BDM1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("360ZhiNao/BDM1.0", 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
- Xet hash:
- 18024f4a7f769d599a42e0365d3bef87a04b2731f6e9e6a24b173b78ff830006
- Size of remote file:
- 1.45 GB
- SHA256:
- 7b6f94fdad69458403e1c0bfca0475b8b65ac9947f185fbe9589efaafb165340
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