Instructions to use Gimbor/han123 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Gimbor/han123 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", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Gimbor/han123") prompt = "A futuristic cyberpunk city street at midnight with neon rain reflecting on the pavement, featuring a sleek robotic panther Han123 prowling through the mist." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- b0d3eefa5d9470b89a3d21cc912d54f99e39f9c145776f269b88499f110d92e2
- Size of remote file:
- 1.26 MB
- SHA256:
- a2f96c73f8acd36d2c43691fdcad0262ca3c19477ced92c8438c4f7b33bd080d
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