kyutai/tts-1.6b-en_fr
text-to-speech model by kyutai
From the publisher
Model card & documentation
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See also the pre-print research paper, the project page, the Colab example, the GitHub repository, and the repository of voices. This is a model for streaming text-to-speech (TTS). Unlike offline text-to-speech, where the model needs the entire text to produce the audio, our model starts to output audio as soon as the first few words from the text have been given as input. This model is actually 1.8B parameters, not 1.6B as the name might suggest. The model architecture is a hierarchical Transformer that consumes tokenized text and generateds audio tokenized by Mimi, see the Moshi paper. The frame rate is 12.5 Hz and each audio frame is represented by 32 audio tokens, although you can use less tokens at inference time for faster generation. The backbone model is 1B parameters, and the depth transformer is 600M parameters and uses partial weight sharing similar to Hibiki. The audio is shifted…
Read the full model card ↗ · Preview checked 2026-10-31T22:21:27.416Z
Inside the original model card — Document outline
- Model Card for Kyutai TTS
- Model Details
- Model Description
- Uses
- Direct Use
- How to Get Started with the Model
- Training Details
- Training Data
- Compute Infrastructure
- Model Card Authors
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Model overview
kyutai/tts-1.6b-en_fr is a text-to-speech model repository published by kyutai on Hugging Face. The source reports the moshi 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
- moshi
- Recent downloads (30 days)
- 68,922
- Cumulative likes
- 385
- Hugging Face trending score
- 1
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- cc-by-4.0
- Access
- Not gated by Hugging Face
- Created
- 2025-06-30T09:12:42.000Z
- Last modified
- 2025-09-11T08:50:45.000Z
Compatibility and lineage
Reported languages: en, fr
Base-model lineage was not included.
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 2026-11-01T06:52:33.137Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.