Instructions to use Muapi/piledriver-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/piledriver-concept with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OnomaAIResearch/Illustrious-xl-early-release-v0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/piledriver-concept") 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:
- 15db1461358b0f6a5727a8fe74e3fa3d2934c19032aed2282f955a894728e57a
- Size of remote file:
- 228 MB
- SHA256:
- 9e6a028c85a3e3b43ae61fe40327b650731fe58bc179e839709e7ae4b1914a1c
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