Instructions to use comin/IterComp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use comin/IterComp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("comin/IterComp", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 2263815806696344fc5eba5d56153c1ab4d30071d3723412cde32e407e70c94d
- Size of remote file:
- 4.26 MB
- SHA256:
- 05f02716a48632c9838005b7e5a5174ae5b7428253467b25255e7ad64b9ca8c7
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