Instructions to use tftgregrge/mpid-uber with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tftgregrge/mpid-uber with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tftgregrge/mpid-uber", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f82a864b2692235e2c236440cab8acc986227c58b2633e069e3a8ffd148037d5
- Size of remote file:
- 246 MB
- SHA256:
- 65f83e1d2bbb8871dacc8885bc5d8ea1d94c2a268cbc59c1543461f081d11bd2
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