Instructions to use Intel/Wan2.2-I2V-A14B-Diffusers-int4-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Intel/Wan2.2-I2V-A14B-Diffusers-int4-AutoRound with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Intel/Wan2.2-I2V-A14B-Diffusers-int4-AutoRound", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43f7ef352db86ebda6c3e29864acd50488a56a5cf0c84a08c0afce00d50d56fc
- Size of remote file:
- 254 MB
- SHA256:
- 39ffe6326a57bbc7c8a704d862e482588e3affc858bdbfc123a91b5ac3a3a42a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.