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:
- 8e8797267294c63e4b87fdbb4df54d24bde7043aa48f4866d672cbc3e16d556d
- Size of remote file:
- 1.04 MB
- SHA256:
- f81a207e83d91410b502a85a6e11d5e15d8c373eac8106db03db2aa519e1fe48
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