Instructions to use juneyoung9/DM-Calib with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use juneyoung9/DM-Calib with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("juneyoung9/DM-Calib", 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
- Xet hash:
- 0f1937827e8bda8a93ed804a5e7968b7bd6bc15e7fa048a46d66e0baca407204
- Size of remote file:
- 198 MB
- SHA256:
- 7ce41e5034b6cd28d4fb90f78734bbf76479301bf7681322248866224ccef4b8
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