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
Download unet/diffusion_pytorch_model.safetensors from comin/IterComp: direct link, hf CLI and curl.
- Browser
- Download file 10.3 GB
-
https://huggingface.co/comin/IterComp/resolve/main/unet/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://comin/IterComp/unet/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/comin/IterComp/resolve/main/unet/diffusion_pytorch_model.safetensors
10.3 GB
- Xet hash:
- 44741446da4caef726e013161afe1511f4c9c666b070418189a681ada76bc64c
- Size of remote file:
- 10.3 GB
- SHA256:
- 7aa0a4274ebc394f0bc24d994d4e0270948d146ef4a5d7b352134e7a9ac0ac7f
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