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:
- 8e5c928530c204a56c72509bad4936aa331236a2e70a83be7a28aa1dde9c21c8
- Size of remote file:
- 1.33 MB
- SHA256:
- 346ba65be87f7a7f53851f7abfced5a72717c7f4df9e5b251d37d82fe417a2b0
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