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:
- 02c106329df618c79164b3de29dccef8f0e9c5b133f8faa146fcf3767a505215
- Size of remote file:
- 18.1 MB
- SHA256:
- feff1f3730b8dae616e3ffd24b2f74dcd9c6776c46e00ac72018e0de74785d06
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