Instructions to use Zenni069/ALTc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Zenni069/ALTc with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RunDiffusion/Juggernaut-Z-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Zenni069/ALTc") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 32a637db3608db115b766f232cf30ddec6b263b547b46e02181491d85c7eddaf
- Size of remote file:
- 246 MB
- SHA256:
- 7f30840dc98e1eef4fda347fef60174952e3af2bd67eb656651d8c39d94c023a
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