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:
- f0a49837ac86baccafc50ff49127b6862539f09fa8672727ef93d93963517b5b
- Size of remote file:
- 195 MB
- SHA256:
- 5d24391c5857305f99a7c2dd7834ebbb477b4a12a6c85eea236fb90741a074cd
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