Key Optimization Strategies to Accelerate Video Generation
Enhancing the efficiency of HunyuanVideoGP operation can be implemented in the following dimensions:
- Hardware Configuration Options: Prioritize the 24GB video memory configuration and use the accompanying high_performance profile. If using an NVIDIA graphics card, make sure the CUDA version is ≥11.7.
- Flash Attention Installation: executed on Linux systems
pip install flash-attn --no-build-isolation, can get 20%-30% speed boost (Windows users can try alternatives) - Batch optimization: Utilizing the multiple generation function, each time you enter 4-6 relevant prompt words, the system will automatically carry out batch processing, which will increase the efficiency by more than 2 times than the single generation.
- Prepare for preprocessing: Early adoption
python preload_models.pyPreload common Lora models to reduce runtime loading delays
Advanced optimization can be done by modifying the launch.sh script to add the--xformersparameter enables the memory-efficient attention mechanism, but requires additional installation of the xformers library.
This answer comes from the articleHunyuanVideoGP: A Hybrid Video Generation Model with Support for Running on Low-End GPUsThe
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