Instructions to use Muapi/assup-flashing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/assup-flashing 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/assup-flashing") 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:
- 72eda962ab33802a555081e4ca6667dd03078601088dd93bbf8dddb15bccc8c3
- Size of remote file:
- 228 MB
- SHA256:
- d0b0d8106600329598b68b7507b83dc451e5e49c15dc877c57ee551ee5eb43e9
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