Instructions to use Muapi/infundibulum-insertion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/infundibulum-insertion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cocktailpeanut/pony-diffusion-v6-xl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/infundibulum-insertion") 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:
- cf73859e43b263993dc7ec2c453f01b645896946847d773d4225fdec586689c6
- Size of remote file:
- 1.94 MB
- SHA256:
- e3024474d894756f4640b4119f7c90063d9def5261f5e5628240a09f127f2d2b
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