Instructions to use emrekoc/trendyol-tts-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use emrekoc/trendyol-tts-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir trendyol-tts-mlx emrekoc/trendyol-tts-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Trendyol TTS MLX Weights
MLX safetensors artifacts for the Apple Silicon / MLX port of Trendyol/Trendyol-TTS.
Code repository: https://github.com/emre-koc/trendyol-tts-mlx
Files
voxcpm2_layers_mlx.safetensorsandvoxcpm2_layers_manifest.json: exported VoxCPM2 local encoder, language-model, residual-LM, DiT/CFM, FSQ/projection, and stop-predictor weights/metadata for the strict MLX runtime.audiovae_decoder_mlx.safetensorsandaudiovae_decoder_manifest.json: exported AudioVAE/vocoder decoder weights/metadata for MLX.
Usage
git clone https://github.com/emre-koc/trendyol-tts-mlx.git
cd trendyol-tts-mlx
/opt/homebrew/bin/python3.11 -m venv .venv
source .venv/bin/activate
pip install -e .
hf download emrekoc/trendyol-tts-mlx --local-dir models/Trendyol-TTS-mlx
trendyol-tts \
--text "Merhaba, Trendyol TTS modelinden Türkçe bir ses örneği dinliyorsunuz." \
--out out.wav \
--device mps \
--backend mlx \
--cfg 2.0 \
--steps 16 \
--max-len 4096
The runtime is currently strict text-only MLX. Prompt/reference audio, streaming, denoiser/enhancer, and voice-cloning paths are intentionally unsupported until explicitly ported.
Hardware compatibility
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