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**Unofficial and unaffiliated** MLX port of the BreezeBlue/Breeze-TTS-2 model, unquantized bf16 variant. > [!IMPORTANT] > Derived from Breeze TTS 2 by BreezeBlue and licensed for research and non-commercial use only. See License.
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This is Chatterbox Multilingual V3, converted to MLX format from ResembleAI/chatterbox using mlx-audio version **0.4.7**. **Note:** This model requires the S3Tokenizer weights from mlx-community/S3TokenizerV2, which will be downloaded automatically.
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This model was converted to MLX format from `ResembleAI/chatterbox-turbo` using mlx-audio version **0.2.8**. Refer to the original model card for more details on the model. Chatterbox supports expressive event tags that can be inserted directly into your text to add natural vocal expressions:
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Clef turns a state (text, JSON, images, or video) plus a schema of typed questions into a probability for every allowed option, in a single forward pass. **It is not a chat model** — `mlx_vlm.generate`, `mlx_lm.generate`, and LM Studio will load the backbone but produce meaningless text. Use the bundled `clef_mlx.py` loader, which runs the backbone and the joint schema head. Measured on an M5 Max with text input. macOS lets the GPU use only about 70–75% of RAM by default, so the minimum RAM is higher than the peak. The 9B variants are much faster; the 27B variants score higher (see the quality check below). Tested with mlx 0.32.3, mlx-lm 0.32.0 and mlx-vlm 0.7.4. `clef_mlx.py` uses mlx-vlm internals, so it warns if you load it with an untested mlx-vlm minor version.
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