Instructions to use Muapi/raphaelz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/raphaelz 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/raphaelz") 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:
- f9c69934bf1ff32d596edca8f021215884421fe18849028c278a14b74a28f528
- Size of remote file:
- 153 MB
- SHA256:
- 9ccf3e4e110eda8989dfd3f60863307eebb03b872d5c1aa83b97c6b3c5e7fb3d
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