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| tags: |
| - ml-intern |
| --- |
| # Astra-TTS Architecture |
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| Architecture design documents for Astra-TTS — a lightweight, high-quality text-to-speech system based on ZipVoice/Zipformer. |
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| ## Documents |
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| | File | Description | |
| |------|-------------| |
| | [`model_a_slim.md`](model_a_slim.md) | **Model A** — ZipVoice naively shrunk to ~55M params. Serves as baseline. | |
| | [`model_b_enhanced.md`](model_b_enhanced.md) | **Model B** — ~55M params with architectural improvements (GQA, DepthSep Conv, Grouped Param Sharing, Dilated ConvNeXt, RoPE, etc.) + inference optimizations (EPSS, Midpoint ODE, SmoothCache). | |
| | [`benchmark_prd.md`](benchmark_prd.md) | **Benchmark PRD** — Full evaluation protocol comparing Original ZipVoice (123M) vs Model A (55M) vs Model B (55M) on LibriTTS. | |
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| ## Goal |
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| Determine whether smart architectural changes at ~55M params can match or exceed a naive shrink, while enabling 6-8× faster inference through combined architecture + inference-time optimizations. |
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| ## Architecture Summary |
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| | | Original ZipVoice | Model A (Slim) | Model B (Enhanced) | |
| |--|-------------------|---------------|-------------------| |
| | **Params** | 123M | ~55M | ~55M | |
| | **Approach** | Full size | Naive shrink | Smart redesign | |
| | **Key changes** | — | Smaller dims/fewer layers | GQA, DepthSep FFN, Grouped Sharing, Dilated ConvNeXt, RoPE, ConvNeXt text refinement, no NLA | |
| | **Inference** | Euler 16 NFE | Euler 16 NFE | Midpoint 4-step + EPSS + SmoothCache | |
| | **Expected speed** | 1× | ~1.5× | **~6-8×** | |
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| ## References |
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| - ZipVoice: [arXiv:2506.13053](https://arxiv.org/abs/2506.13053) |
| - Zipformer: [arXiv:2310.11230](https://arxiv.org/abs/2310.11230) |
| - Supertonic 3: [Supertone/supertonic-3](https://huggingface.co/Supertone/supertonic-3) |
| - F5-TTS: [arXiv:2410.06885](https://arxiv.org/abs/2410.06885) |
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| ## License |
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| Apache-2.0 |
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| <!-- ml-intern-provenance --> |
| ## Generated by ML Intern |
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| This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub. |
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| - Try ML Intern: https://smolagents-ml-intern.hf.space |
| - Source code: https://github.com/huggingface/ml-intern |
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| ## Usage |
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| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model_id = "Praha-Labs/Astra-TTS-Arch" |
| tokenizer = AutoTokenizer.from_pretrained(model_id) |
| model = AutoModelForCausalLM.from_pretrained(model_id) |
| ``` |
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| For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class. |
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