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", 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:
- 502c9d6c5e96bb82c9a6a04b3e035d511425a147937a9d50191ada0d3a09cf8d
- Size of remote file:
- 446 kB
- SHA256:
- 984efa12db10f378f37ba0576be90517658ed5c4a4146f2483121e9ae8fbd800
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