Image-to-Video
Diffusers
Safetensors
English
4d-generation
image-to-4d
diffusion
novel-view-synthesis
point-trajectory
Instructions to use Yanran21/MoGe4D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yanran21/MoGe4D 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("Yanran21/MoGe4D", torch_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:
- fb2fc510c0bc066274d7b0983912a2fd433b1ccef0ed62ed1a7a66b0f293fc87
- Size of remote file:
- 1.46 GB
- SHA256:
- 34dd55e38a8e853849f25748feedf515c5241d6666b6c2abfd22322252968daa
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