Instructions to use diff-mining/cardb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diff-mining/cardb with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diff-mining/cardb", 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:
- 825eae0e573c8a7a0d3f6202cee7c519b00bff7385de9744c4b8e8d0d9360b6b
- Size of remote file:
- 3.44 GB
- SHA256:
- 276335d7092487d240538444ff53b16d6bf265873ecf0cda3c564097303ecb5b
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