Safetensors

Launch MOSS-TTS For Beginners

Launch MOSS-TTS For Beginners

To get this model running locally in no time, utilize the built-in WSL tools.

Follow the guidelines below to continue.

The system automatically triggers a cloud download for all heavy weights.

There is no manual tuning required; the builder deploys the best matching configuration.

🔗 SHA sum: d665cbec2038e5ce42cf93f01bb89527 | Updated: 2026-06-26
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  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: minimum 16 GB for stable 8B model loading
  • Storage:100 GB free space for HuggingFace cache folder
  • GPU: high memory bandwidth GPU for next-gen local AI pipeline

MOSS-TTS is a next‑generation text‑to‑speech model that employs a transformer‑based architecture for ultra‑realistic voice generation. It supports multiple languages and dialects, delivering natural prosody and emotion through its advanced phoneme tokenizer and context‑aware encoder. The model achieves *real‑time* synthesis on consumer hardware, thanks to optimized inference kernels and a compact parameter set. A built‑in speaker embedding system allows users to personalize voice characteristics, while a *high‑fidelity* loss function ensures minimal artifacts. The following table summarizes key technical specifications for quick reference.

Parameter Value
Model Type Transformer‑based TTS
Supported Languages 30+ languages & dialects
Parameter Count 150M
Synthesis Speed ≤ 50 ms per 100 characters
Speaker Embeddings Customizable voice profiles
  • Setup tool configuring MemGPT memory layers alongside persistent local GGUF instances
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  • Downloader pulling compact 2-bit quantization variants for rapid text prototyping simulation workflows
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