Feature Extraction
Transformers
Safetensors
MLX
moss-audio-tokenizer
audio
audio-tokenizer
neural-codec
moss-tts-family
MOSS Audio Tokenizer
speech-tokenizer
mlx-audio
custom_code
Instructions to use mlx-community/MOSS-Audio-Tokenizer-Nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlx-community/MOSS-Audio-Tokenizer-Nano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mlx-community/MOSS-Audio-Tokenizer-Nano", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mlx-community/MOSS-Audio-Tokenizer-Nano", trust_remote_code=True, dtype="auto") - MLX
How to use mlx-community/MOSS-Audio-Tokenizer-Nano with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir MOSS-Audio-Tokenizer-Nano mlx-community/MOSS-Audio-Tokenizer-Nano
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
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base_model: OpenMOSS-Team/MOSS-Audio-Tokenizer
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# mlx-community/MOSS-Audio-Tokenizer
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This model was converted to MLX format from [`OpenMOSS-Team/MOSS-Audio-Tokenizer`](https://huggingface.co/OpenMOSS-Team/MOSS-Audio-Tokenizer) using mlx-audio version **0.4.0**.
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Refer to the [original model card](https://huggingface.co/OpenMOSS-Team/MOSS-Audio-Tokenizer) for more details on the model.
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# MossAudioTokenizer
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base_model: OpenMOSS-Team/MOSS-Audio-Tokenizer
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# mlx-community/MOSS-Audio-Tokenizer-Nano
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This model was converted to MLX format from [`OpenMOSS-Team/MOSS-Audio-Tokenizer-Nano`](https://huggingface.co/OpenMOSS-Team/MOSS-Audio-Tokenizer-Nano) using mlx-audio version **0.4.0**.
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Refer to the [original model card](https://huggingface.co/OpenMOSS-Team/MOSS-Audio-Tokenizer-Nano) for more details on the model.
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# MossAudioTokenizer
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