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
Fix pipeline tag
#1
by nielsr HF Staff - opened
README.md
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license: mit
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library_name: diffusers
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---
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<p align="center">
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2502.10248},
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```
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---
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library_name: diffusers
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license: mit
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pipeline_tag: text-to-video
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---
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<p align="center">
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2502.10248},
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}
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```
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