Instructions to use SidXXD/barn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/barn with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/barn", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <new1> barn" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 197dfe44641ef1f765dd27b99afb75203a800cf76358a5300ab2f71eb045365b
- Size of remote file:
- 76.7 MB
- SHA256:
- 9a8552256c712ce3c6fef4c27632311530d25a6d0685852c192630829a01915f
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