Feature Extraction
Transformers
Safetensors
moss-audio-tokenizer
audio
audio-tokenizer
neural-codec
moss-tts-family
MOSS Audio Tokenizer
speech-tokenizer
trust-remote-code
custom_code
Instructions to use OpenMOSS-Team/MOSS-Audio-Tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMOSS-Team/MOSS-Audio-Tokenizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="OpenMOSS-Team/MOSS-Audio-Tokenizer", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenMOSS-Team/MOSS-Audio-Tokenizer", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
update config
Browse files- config.json +1 -1
config.json
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"positional_embedding": "rope"
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}
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],
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"model_type": "
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"quantizer_kwargs": {
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"codebook_dim": 8,
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"codebook_size": 1024,
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"positional_embedding": "rope"
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}
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],
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"model_type": "moss-audio-tokenizer",
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"quantizer_kwargs": {
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"codebook_dim": 8,
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"codebook_size": 1024,
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