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:
- 24add46edd1e4852f5491493f71b7ca558814dabef52c7395a536537d8f72938
- Size of remote file:
- 246 MB
- SHA256:
- 4d800c8bc7d25ddcffc82f5a7d9986b3cbd48ba2afdc1aca2bdb42ffdf78f352
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