MisoLabs/MisoTTS
Summary
Miso Labs releases Miso TTS 8B, a text-to-speech model based on the Sesame CSM architecture with a Llama 3.2-style backbone, designed for high-quality conversational speech generation and voice continuation.
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MisoLabs/MisoTTS · Hugging Face
Source: https://huggingface.co/MisoLabs/MisoTTS
https://huggingface.co/MisoLabs/MisoTTS#miso-tts-8bMiso TTS 8B
https://huggingface.co/MisoLabs/MisoTTS#model-introductionModel Introduction
Miso TTS 8B is a text-to-speech model based on the Sesame CSM architecture. It generates Mimi audio codes from text and optional audio context, using a large Llama 3.2-style backbone and a smaller autoregressive audio decoder.
The model is designed for high-quality conversational speech generation and voice continuation from prompt audio. This repository contains the inference code, model definition, and setup instructions for running Miso TTS locally.
https://huggingface.co/MisoLabs/MisoTTS#quickstartQuickstart
To run the model, use the inference code at ourpublic repository, or try our demo at misolabs.ai.
https://huggingface.co/MisoLabs/MisoTTS#model-summaryModel Summary
ItemValueModelMiso TTS 8BOrganizationMiso LabsTaskText-to-speechArchitectureSesame-style CSMBackbonellama\-8BAudio decoderllama\-300MText vocabulary128,256Audio vocabulary2,051Audio codebooks32Audio tokenizerMimiMax sequence length2,048
https://huggingface.co/MisoLabs/MisoTTS#architectureArchitecture
Miso TTS 8B uses two transformer components:
- A large backbone transformer that consumes text/audio-frame embeddings.
- A smaller decoder transformer that autoregressively predicts higher-order audio codebooks within each frame.
Codebook 0 is predicted from the backbone hidden state, while codebooks 1 through 31 are predicted by the audio decoder autoregressively in codebook depth.
https://huggingface.co/MisoLabs/MisoTTS#linksLinks
- Website:misolabs.ai
- Hugging Face:MisoLabs/MisoTTS
- GitHub:MisoLabsAI
- X:@MisoLabsAI
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