Instructions to use martineux/coco61 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use martineux/coco61 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("martineux/coco61", 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:
- 609cd8125fea59f0a51cae4509c126bae7b7d6f1ed2e83e7ea155a570796768d
- Size of remote file:
- 167 MB
- SHA256:
- 94b04ed4a6f2b057ebf5820cc8429ef06c17ff2b58c5da74d40245124bb123b5
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