Instructions to use diffusers-internal-dev/private-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-internal-dev/private-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers-internal-dev/private-model", 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:
- 5a91be61fa7e2352ea4783ce02c1a54b93310708e34f40497d1bcf8ad0085f28
- Size of remote file:
- 335 MB
- SHA256:
- d972e5c4aa354ca9eeee7517bd8b6a7da1c2df2cdf8d657723f689ca1ad65679
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