Instructions to use cutycat2000x/InterDiffusion-Midj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cutycat2000x/InterDiffusion-Midj with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cutycat2000x/InterDiffusion-Midj", 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:
- dee22fa870b5157f427f251943c7015c99e2ebdb1616931a6c98e57d20a4081b
- Size of remote file:
- 246 MB
- SHA256:
- a042a04b6edb86255f8802065ac0a2c13e927bbacf652dc92d937095d8f3618a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.