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
Commit ·
b1dd2ae
1
Parent(s): eff8e23
fix an import bug
Browse files
modeling_moss_audio_tokenizer.py
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@@ -25,8 +25,8 @@ import torch
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import torch.nn as nn
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import torch.nn.functional as F
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from .
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from .
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from .configuration_moss_audio_tokenizer import MossAudioTokenizerConfig
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import torch.nn as nn
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import torch.nn.functional as F
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from transformers.modeling_utils import PreTrainedAudioTokenizerBase
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from transformers.utils import ModelOutput, auto_docstring, logging
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from .configuration_moss_audio_tokenizer import MossAudioTokenizerConfig
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