Instructions to use aimalias/jgu1l with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aimalias/jgu1l with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("aimalias/jgu1l") prompt = "A cinematic shot of a JGU1L woman wearing holographic armor, standing atop a neon-lit skyscraper in a rainy cyberpunk metropolis." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7e41c18e1dbe59d24c6f92f869d69fb9af3501aa05f8426f17000f2a36ef95c3
- Size of remote file:
- 195 MB
- SHA256:
- 8e9bd9652084540ba218e54d17dd0c1000cb22efa05d40615bcc06b66beb566a
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