Instructions to use duja1/tjmo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use duja1/tjmo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("duja1/tjmo", 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:
- 695479c0201c4019343bb51ac66f5f2793914f2f27b9ee06e74ea08a2f033ae0
- Size of remote file:
- 492 MB
- SHA256:
- c375e20ad8453f4595509fd531f8ca243816a32a04340f39f5bc5360347c40f8
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