Instructions to use wolfer45/pronebonev2-high-t2v-wan22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wolfer45/pronebonev2-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/pronebonev2-high-t2v-wan22") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 920efb4e7fcc306659e603c914abbef51258016b3c7883c10e44b8e1d2c28075
- Size of remote file:
- 614 MB
- SHA256:
- 280948e0a9a14ce58f49a3abb8ddd360202de4cd18b16ff384b3231ad6e443e7
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