Preparation for installation
Before using Step-Video-T2V, you need to make sure that your system meets the following conditions: Python 3.10 environment, Git version control system, recommended Conda management environment.
Detailed installation steps
- Cloning GitHub repositories:
git clone https://github.com/stepfun-ai/Step-Video-T2V.git - Go to the project catalog:
cd Step-Video-T2V - Create a virtual environment:
conda create -n stepvideo python=3.10
conda activate stepvideo - Install the dependencies:
pip install -e .
Optionally install the flash-attn acceleration module:pip install flash-attn --no-build-isolation
hardware requirement
The project supports single-GPU inference and quantization techniques, which can significantly reduce graphics memory requirements. It is recommended to use an NVIDIA GPU and install the CUDA driver, see the GitHub documentation for specific configuration requirements.
This answer comes from the articleStep-Video-T2V: A Vincennes Video Model Supporting Multilingual Input and Long Video GenerationThe
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