Instructions to use wolfer45/scissoringv3-low-t2v-wan22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wolfer45/scissoringv3-low-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-low-t2v-wan22") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- deae1b59c980ee7878a40a870839a88838be9eca26b55bb851493369fc91d23a
- Size of remote file:
- 614 MB
- SHA256:
- 0f7ec41b5a99055e9db15d839b919a0d9d2d579908ca27dd395fd0f0a19390f0
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