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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a65ec398a8b623705d6d31be04340bc8fd6e762bb0fe36e2bee14c6d14afa155
- Size of remote file:
- 5 GB
- SHA256:
- 037f441ed30a0ab59f6049de83b824a1b3bd6feb7dbd46c3fbca41fc2f649f28
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