StyleTTS2
| Property | Value |
|---|---|
| License | MIT |
| Language | English |
| Base Model | yl4579/StyleTTS2-LibriTTS |
| Pipeline | Text-to-Speech |
What is styletts2?
StyleTTS2 is an ONNX-converted text-to-speech model derived from the original StyleTTS2-LibriTTS PyTorch implementation. This model has been specifically optimized for CPU-based inference and is structured in four parts to enable lazy loading. It represents a direct conversion of the original model without any modifications to its weights.
Implementation Details
The model is implemented as an ONNX conversion, designed specifically for CPU deployment. It's worth noting that this implementation prioritizes accessibility over performance optimization, particularly in GPU environments where the original PyTorch model demonstrates superior performance.
- Direct ONNX conversion from StyleTTS2-LibriTTS
- Chunked into four parts for efficient lazy loading
- Optimized for CPU-based inference
- Maintains original model weights and architecture
Core Capabilities
- English text-to-speech synthesis
- CPU-friendly implementation
- WebUI integration support
- Efficient lazy loading through chunked architecture
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its CPU-optimized ONNX implementation, making it particularly suitable for environments where GPU resources are limited or unavailable. It powers a dedicated WebUI for TTS inference on CPU, making it accessible for broader deployment scenarios.
Q: What are the recommended use cases?
The model is best suited for CPU-based text-to-speech applications, particularly in web environments. However, for GPU-accelerated environments, the original PyTorch implementation may be more appropriate due to better performance characteristics.
