Instructions to use dg845/univnet-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dg845/univnet-dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dg845/univnet-dev")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("dg845/univnet-dev") model = AutoModel.from_pretrained("dg845/univnet-dev") - Notebooks
- Google Colab
- Kaggle
Upload preprocessor_config.json
Browse filesUpdate feature extractor config (calculate spectrogram_zero from other config values)
- preprocessor_config.json +0 -1
preprocessor_config.json
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"padding_value": 0.0,
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"return_attention_mask": true,
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"sampling_rate": 24000,
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"spectrogram_zero": -11.5129,
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"win_function": "hann_window",
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"win_length": 1024
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}
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"padding_value": 0.0,
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"return_attention_mask": true,
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"sampling_rate": 24000,
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"win_function": "hann_window",
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"win_length": 1024
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}
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