Instructions to use tuwonga/dbluth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tuwonga/dbluth with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tuwonga/dbluth", torch_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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c87c2c32051136a006375689b03c6872a1e6cf4a9f3836f0c3e5721064861a99
- Size of remote file:
- 335 MB
- SHA256:
- b041e936f05862e651247310cc36f5e9cf12de1e94670ce70402dd03c624a7c4
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