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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 718d615ecf322852a286bfcaec9d6eb20b5317f2ead0720462d74c67248f7ebc
- Size of remote file:
- 246 MB
- SHA256:
- 774ae13c9fb2a4feff1fd102a128b5b0f73a95fcd53e8dc4448e744afd177bb1
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