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:
- db5edc75e31dcf657fc4c141ea0ae20759a6b967e2a6e1583c13b1c931e5948d
- Size of remote file:
- 1.39 GB
- SHA256:
- 02334b8b52dfbfbe9afc4bbae93263d891a6a97b50ca7c8aac1aebf98ce6597b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.