Instructions to use martineux/bbb2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use martineux/bbb2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("martineux/bbb2", 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:
- d761140404039c43cf6f4614fbae77fc21d3d61c6702c4ddb069cbc088f59f9a
- Size of remote file:
- 167 MB
- SHA256:
- d0a75cb258919bfb5613b2b715c474688ba50e296e9e4cf2341220a8a6c1f58f
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