Instructions to use wolfer45/scissoringv3-high-t2v-wan22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wolfer45/scissoringv3-high-t2v-wan22 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/scissoringv3-high-t2v-wan22") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 393ddbdcada0cf25a67eb6c995c7497a85351d8e5847f4af52d37caad6d53d21
- Size of remote file:
- 614 MB
- SHA256:
- 2883a9e92e2ea857d510c60f84ed2229712a8b97958ca55d9a4c577a1f3e90b4
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