Audio-to-Audio
Transformers
Safetensors
dashengtokenizer
feature-extraction
audio-classification
signal-processing
custom_code
Instructions to use mispeech/dashengtokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mispeech/dashengtokenizer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mispeech/dashengtokenizer", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Heinrich Dinkel commited on
Commit ·
5340ead
1
Parent(s): 0f35cd3
updated
Browse files- notebook.ipynb +1 -1
notebook.ipynb
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" classifier.to(device)\n",
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" \n",
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" # Training setup\n",
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" optimizer = torch.optim.Adam(classifier.parameters(), lr=
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" criterion = nn.CrossEntropyLoss()\n",
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" \n",
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" # Training loop\n",
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" classifier.to(device)\n",
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" \n",
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" # Training setup\n",
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" optimizer = torch.optim.Adam(classifier.parameters(), lr=8e-3)\n",
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" criterion = nn.CrossEntropyLoss()\n",
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" \n",
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" # Training loop\n",
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