Image-to-Video
Diffusers
Safetensors
MagiHumanPipeline
text-to-video
image-text-to-video
text-to-audio
text-to-audio-video
image-to-audio-video
image-text-to-audio-video
multimodal
Instructions to use SII-GAIR/daVinci-MagiHuman-Base-1080p with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SII-GAIR/daVinci-MagiHuman-Base-1080p 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("SII-GAIR/daVinci-MagiHuman-Base-1080p", 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
- Xet hash:
- 6f01bc4289b396e709088ce7f8aacb5ea9a4e9057fa99b36e1d86d621b01690f
- Size of remote file:
- 4.96 GB
- SHA256:
- 16b7f883831fa9c805551978b63339a95d69276caf79ca88cc73ba077708de11
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