Instructions to use bezzam/xcodec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bezzam/xcodec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bezzam/xcodec2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bezzam/xcodec2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload feature extractor
Browse files- preprocessor_config.json +1 -0
preprocessor_config.json
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{
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"feature_size": 80,
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"hop_length": 320,
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"n_fft": 512,
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{
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"feature_extractor_type": "Xcodec2FeatureExtractor",
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"feature_size": 80,
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"hop_length": 320,
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"n_fft": 512,
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