Instructions to use babkasotona/1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use babkasotona/1b 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/1b", dtype=torch.bfloat16, device_map="cuda") prompt = "sdxs-1b" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Rendering notebook...
- Xet hash:
- 84d6ea3a5c6674af1b6b3c18993d4b6b8593563478df553d7a9ec3f3681da60d
- Size of remote file:
- 54.8 MB
- SHA256:
- 4383d01980c5ac091001d6148846df7736be3424d96efe604244353ea3ff9303
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