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:
- dccd0fc4ce4ed2ffe5b62987992c85027c5638ab2ac7ec86a05e3fa895ecce37
- Size of remote file:
- 1.42 MB
- SHA256:
- 1651b60e05d114f016f606c5702a0629dc147759ae51e588ecc83d4ec471c8bd
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