Instructions to use stepfun-ai/stepvideo-ti2v with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stepfun-ai/stepvideo-ti2v 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("stepfun-ai/stepvideo-ti2v", 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
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## π₯π₯π₯ News!!
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* Mar 17, 2025: π We release the inference code and model weights of Step-Video-TI2V. [Download](https://huggingface.co/stepfun-ai/stepvideo-ti2v)
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* Mar 17, 2025: π We have made our technical report available as open source. [Read](https://arxiv.org/abs/2503.11251)
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## π§ 4.2 Dependencies and Installation
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## π₯π₯π₯ News!!
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* Mar 17, 2025: π We release the inference code and model weights of Step-Video-TI2V. [Download](https://huggingface.co/stepfun-ai/stepvideo-ti2v)
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* Mar 17, 2025: π We release a new TI2V benchmark [Step-Video-TI2V-Eval](https://github.com/stepfun-ai/Step-Video-TI2V/tree/main/benchmark/Step-Video-TI2V-Eval)
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* Mar 17, 2025: π Step-Video-TI2V has been integrated into [ComfyUI-Stepvideo-ti2v](https://github.com/stepfun-ai/ComfyUI-StepVideo). Enjoy!
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* Mar 17, 2025: π We have made our technical report available as open source. [Read](https://arxiv.org/abs/2503.11251)
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## π§ 4.2 Dependencies and Installation
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