Instructions to use AxlMk2/PPEM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AxlMk2/PPEM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AxlMk2/PPEM", 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:
- 4960fcd10725df7c1eac972de623c89780fc57df0d2d7a0857ccda02bb6a82ff
- Size of remote file:
- 246 MB
- SHA256:
- 30342d29c53e6159659de9c1e3d7a71268e5eeb53e5431b13a079403dac8fa87
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.