Instructions to use intel-ai/Wan2.2-I2V-A14B-Diffusers-NVFP4-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use intel-ai/Wan2.2-I2V-A14B-Diffusers-NVFP4-AutoRound with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("intel-ai/Wan2.2-I2V-A14B-Diffusers-NVFP4-AutoRound", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Download tokenizer/tokenizer.json from intel-ai/Wan2.2-I2V-A14B-Diffusers-NVFP4-AutoRound: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/intel-ai/Wan2.2-I2V-A14B-Diffusers-NVFP4-AutoRound/resolve/main/tokenizer/tokenizer.json
- Command line
-
hf download hf://intel-ai/Wan2.2-I2V-A14B-Diffusers-NVFP4-AutoRound/tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/intel-ai/Wan2.2-I2V-A14B-Diffusers-NVFP4-AutoRound/resolve/main/tokenizer/tokenizer.json
16.8 MB
- Xet hash:
- e93e58ffae259ad00bdf467b4d89cc7506133978a98bdb74edc1d71f9668b929
- Size of remote file:
- 16.8 MB
- SHA256:
- 1c55256ddc61e65d42614511254cee7ed55a1783846ddbb0967da2ac20bf6970
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.