Instructions to use duja1/mjjjj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use duja1/mjjjj 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/mjjjj", 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:
- 8153cfd5728463a398027e769c6b9a3257edaec84547d61b171345acfa61752a
- Size of remote file:
- 3.44 GB
- SHA256:
- 80eccc16b70ade792c68bdfac63277ff2ff0aacb20f9ee4fcb87c876a18453fc
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