Instructions to use wolfer45/pronebonev2-low-t2v-wan22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wolfer45/pronebonev2-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/pronebonev2-low-t2v-wan22") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ec760a80ac18b23d1538614d63673a571b05a8ba5f7978438a6982709c9c9f97
- Size of remote file:
- 614 MB
- SHA256:
- 1db535780fa864f420455851f8d9f3df8c517d97b562256bbe9f88344d932b7f
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