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:
- f277061c8854c8e9dcb8f6b70ab0c4f428e873ddc8aa1766a6ec486f833911f6
- Size of remote file:
- 195 MB
- SHA256:
- c0da7b21413954812d6b3a5bba1dfd52d3992b5867e44a0a4139d74c200b8b23
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