Instructions to use yngpaun/g1nger666 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yngpaun/g1nger666 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ostris/wan22_i2v_14b_orbit_shot_lora", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("yngpaun/g1nger666") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 062e052f80137ee735b92b455b616318c0c3621f46d34582bf9fd8692530cf4f
- Size of remote file:
- 153 MB
- SHA256:
- b323a5e7ec53c8f5a99e7e64069f9c394f8f752bf5501f58b17930419de5afbb
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