Instructions to use ionet-official/bc8-alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ionet-official/bc8-alpha with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ionet-official/bc8-alpha", 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
- Draw Things
- DiffusionBee
- Xet hash:
- d13266e3c807ea213b305db2d6b595776affc85a76dca9ffcdaa2167189afbf8
- Size of remote file:
- 492 MB
- SHA256:
- 1a544b59d46af5d2b99f013e8f79d6d0835f5b8d96a1a279f4be68d949738696
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