Image-to-Video
Diffusers
Safetensors
English
text-to-video
anime
video-generation
diffusion-transformer
flow-matching
wan
commercial-use
Instructions to use aidealab/AnimeGen-I2V with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aidealab/AnimeGen-I2V 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("aidealab/AnimeGen-I2V", 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 sample_1.png from aidealab/AnimeGen-I2V: direct link, hf CLI and curl.
- Browser
- Download file 1.32 MB
-
https://huggingface.co/aidealab/AnimeGen-I2V/resolve/main/sample_1.png
- Command line
-
hf download hf://aidealab/AnimeGen-I2V/sample_1.png
-
curl -L -o sample_1.png https://huggingface.co/aidealab/AnimeGen-I2V/resolve/main/sample_1.png
1.32 MB

- Xet hash:
- ed4578c45fb5cc348b201a258fa9017ccab2aec7841b4ca0517faabdcf4ac157
- Size of remote file:
- 1.32 MB
- SHA256:
- b4ed7ab44ac5c591b408cb5454843096288d0e0b688db9b162e74ad8d99a176f
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