Instructions to use EnD-Diffusers/Poltergeist1pt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EnD-Diffusers/Poltergeist1pt2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EnD-Diffusers/Poltergeist1pt2", 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:
- fd860cbd10cc3a1ba963c2cde7035df7fe5340980c3e7e48c08dedc381a4d8f2
- Size of remote file:
- 167 MB
- SHA256:
- eb6516ab7e1104d5d1a174a4d65c57835ae38061531d0a2192103aecfb790cc1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.