Image-to-Video
Diffusers
Safetensors
English
Chinese
ImageToVideoPipeline
video generation
conversational video generation
talking human video generation
Instructions to use ssbtech/models-part1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ssbtech/models-part1 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("ssbtech/models-part1", 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:
- 8aa2b75ce033315c8cd2eb5dc360a60b5d7cb571452a200273acd760af70b7e8
- Size of remote file:
- 1.18 MB
- SHA256:
- dca19575d5c512b93d0eab2359cc75878da2064d4ef0e1f44aaf6accc04d6e0a
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