Instructions to use wolfer45/ballkickinglow-wan22-i2v with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wolfer45/ballkickinglow-wan22-i2v 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("wolfer45/ballkickinglow-wan22-i2v") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 35260b9d86ab69f7603e287630cd2fda296d787bb1ccd4eabe50912c8cc28699
- Size of remote file:
- 153 MB
- SHA256:
- 58bcb5bc4d088beb0060d470573271697027937b57f2fd92633def65d551e371
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