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:
- b7765297a911797ecffb14f48349d905e440b1a2d679de38f0bce5dbcb6428d9
- Size of remote file:
- 335 MB
- SHA256:
- 1cbd2bce272bcb4709a6534abf4180c3747ba513834cebe11b6ed48f7a9c43ac
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