Instructions to use diffusersfan/prmj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusersfan/prmj with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusersfan/prmj", 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:
- 2860c3d658f6c159e00fc2f1835e61f408b1f4a1c9f3749d75131062b880c442
- Size of remote file:
- 1.73 GB
- SHA256:
- 1f03304cdc33e66216a004f1110185ec2cb6c954a5471c3d54730df316e03301
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