Instructions to use Muapi/hibiscus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/hibiscus with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/hibiscus") 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:
- dddb037d51449b4569428ddf482b9da9541786444f70c0ba0c6c7017ca924917
- Size of remote file:
- 560 kB
- SHA256:
- fbeba09d2dd5be002ca0a4896c779b05c3224c06a32d68ce721f6ae53af95bd2
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