Instructions to use babkasotona/2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use babkasotona/2b with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("babkasotona/2b", 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
Rendering notebook...
- Xet hash:
- 79acb7c2a42351ee9eafd56982be1cfc1ba0f460f13b659d97e5110d76c54bac
- Size of remote file:
- 8.19 kB
- SHA256:
- 774dc5b6f2f55e8b4e925e5ba984f73b18e2c096b6c1df4bfe0075aa51a56258
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