Instructions to use dhdbsrlw/pet-monga with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dhdbsrlw/pet-monga with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dhdbsrlw/pet-monga", 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:
- b565d0332e0fe26e470983a2299692ba95b4998e252c33b258ad7ebde200665d
- Size of remote file:
- 246 MB
- SHA256:
- 6edd9ff7b02b3bbb19ba4fa637475ff378c4a5b46cf578277c93a8de7cffb048
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.