Optimized solution for low performance hardware operation
Orpheus-TTS offers a variety of solutions for under-configured hardware:
- CPU mode operation: Use the official orpheus-cpp tool to run in a pure CPU environment via llama.cpp. Note: 1) Performance will be significantly lower than GPU 2) Only suitable for light testing or simple tasks.
- Cloud Deployment: For the case of insufficient local hardware, it is recommended to use the vLLM framework to deploy in the cloud, which can be used to realize the function through API calls.
- Model quantification: Community-contributed quantized versions can reduce the graphics memory footprint, e.g., a model using 4-bit quantization can reduce the graphics memory requirement from 12GB to 6GB.
- Simplified model: Replace the full model with the smaller model from the research-release version.
Implementation Steps: 1) Prioritize testing CPU mode 2) Consider cloud-based solutions if results are insufficient 3) Hardware upgrades are recommended for long-term use.
This answer comes from the articleOrpheus-TTS: Text-to-Speech Tool for Generating Natural Chinese SpeechThe
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