Instructions to use Muapi/sarashi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/sarashi with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/sarashi") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 9b19025b6c1d76a6bd616edf1301589aa7b35f4f454cb82b0203e3abc0e6a0b4
- Size of remote file:
- 303 kB
- SHA256:
- 5885046c670594d188c62195e2d04d8ef6b18780ac09c2adbe0c29bf8acb9260
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