Instructions to use leotest2026/wan22_readyforbj_low with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use leotest2026/wan22_readyforbj_low 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", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("leotest2026/wan22_readyforbj_low") prompt = "A woman walks toward the viewer. She pulls her hair back and holds it up with both hands. She gets down on her knees. Then she opens her mouth wide and extends her tongue." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- bb398551124579b09efc08d453834c71fb8f93ed29a14715ca36b0bd67e0422c
- Size of remote file:
- 307 MB
- SHA256:
- 7ddba644de1d6822ca7f83d69adce8862218e3841ee69fcc9227ecdbd8161a20
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