Instructions to use mekrod/dlh9-pX2-p2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mekrod/dlh9-pX2-p2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mekrod/dlh9-pX2-p2", 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:
- 3e552543cc8adb68828826d39b9864e6a3a593b38ff209e0e89f5438fb2f923d
- Size of remote file:
- 492 MB
- SHA256:
- ab7145aebefa83879ac82785ba51c7e6f509df531808d17e1633e52d43b6db0e
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