Instructions to use Icepoz/icepoz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Icepoz/icepoz 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-Turbo,krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Icepoz/icepoz") prompt = "TOK" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 8fc05e1ed7ed0a4b86844fa2a319e95eb9fb9315555a9d308dc840f90b288cd6
- Size of remote file:
- 1.33 MB
- SHA256:
- 2bffe0fa997544077005a607118e937a1da5d045a741a8af90cb5e9fdb828d88
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