A Practical Guide to Simplify Deployment and Use
For small teams with limited resources, the following low-threshold implementation options are recommended:
- Infrastructure options:
- Use a cloud server with Ubuntu pre-installed (e.g. AWS EC2 g5.2xlarge instance)
- Download the Docker image directly (if provided by the community) to avoid complex environment configuration
- Prioritize the HuggingFace Inference API to reduce local deployment pressure
- Simplified workflow:
- Create a library of commonly used voice templates to reduce the time spent selecting each reference audio
- Run critical code with Google Colab to avoid local GPU inputs
- commander-in-chief (military)
make buildThe process is broken down into step-by-step checkpoints
- Community Resource Utilization:
- Check GitHub Issues regularly for FAQs!
- Participate in the Discord community for live technical support
- Reuse training profiles shared by others
- Long-term maintenance strategy:
- Build automated monitoring scripts to track API service status
- Regular quality sampling of generated speech
- Retain model weights across versions for easy rollback
Through these measures, teams of less than 3 people can also efficiently use Muyan-TTS for daily content production.
This answer comes from the articleMuyan-TTS: Personalized Podcast Speech Training and SynthesisThe
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