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:
- 8c08ecbeda8258c2b6e90b24def93b6a67a966c6d22092dbe79ca966b7b6ef49
- Size of remote file:
- 48 MB
- SHA256:
- bd957d053fe62db318acdb9637206ec7d7d468c9b8bea084140ebd94c23cbf16
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