Instructions to use Muapi/posing-dynamics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/posing-dynamics 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/posing-dynamics") 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:
- d78e34695765788d636d7c3b6d2295dc0c7a06609c55d6ccb59e911c69f8bba3
- Size of remote file:
- 39.8 MB
- SHA256:
- 00168d8cc4f154d6804d8a07f912d038bbb9a9c9bbdfcaafa94adb369ea26bf7
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