Aratako/MioTTS-2.6B
text-to-speech model by Aratako
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Model card & documentation
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[](https://huggingface.co/collections/Aratako/miotts) [](https://github.com/Aratako/MioTTS-Inference) MioTTS-2.6B is a lightweight, high-speed Text-to-Speech (TTS) model based on an LLM architecture. It is designed to generate high-quality speech in English and Japanese while maintaining low latency and minimal resource usage. This model supports zero-shot voice cloning and is built on top of the efficient neural audio codec MioCodec-25Hz-24kHz. We offer a range of model sizes to suit different performance and resource requirements. We provide a dedicated repository for inference, including installation instructions and example WebUI. 👉 GitHub: Aratako/MioTTS-Inference…
Read the full model card ↗ · Preview checked 2026-09-20T06:44:41.669Z
Inside the original model card — Document outline
- MioTTS-2.6B: Lightweight & Fast LLM-based TTS
- 📊 MioTTS Family
- 🌟 Key Features
- 🚀 Inference
- 🎧 Audio Samples
- 🏗️ Training Details
- 📜 License & Ethical Restrictions
- License
- Ethical Considerations & Limitations
- 🙏 Acknowledgments
- 🖊️ Citation
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Model overview
Aratako/MioTTS-2.6B is a text-to-speech model repository published by Aratako on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-speech
- Library
- transformers
- Recent downloads (30 days)
- 15,466
- Cumulative likes
- 81
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 2,593,389,568
- Architecture
- Lfm2ForCausalLM
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-02-09T08:18:35.000Z
- Last modified
- 2026-02-10T08:28:35.000Z
Compatibility and lineage
Reported languages: ja, en
Reported base models: LiquidAI/LFM2-2.6B
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-21T06:36:51.034Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.