Instructions to use hf-audio/xcodec-hubert-librispeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-audio/xcodec-hubert-librispeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-audio/xcodec-hubert-librispeech")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("hf-audio/xcodec-hubert-librispeech") model = AutoModel.from_pretrained("hf-audio/xcodec-hubert-librispeech") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -11,7 +11,7 @@ This codec is part of the X-Codec family of codecs as shown below:
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| Model checkpoint | Semantic Model | Domain | Training Data |
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| [xcodec-hubert-librispeech](https://huggingface.co/hf-audio/xcodec-hubert-librispeech) (this model) | [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) | Speech | Librispeech |
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| [xcodec-wavlm-mls](https://huggingface.co/hf-audio/xcodec-wavlm-mls) | [microsoft/wavlm-base-plus](https://huggingface.co/microsoft/wavlm-base-plus)| Speech | MLS English |
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| [xcodec-wavlm-more-data](https://huggingface.co/hf-audio/xcodec-wavlm-more-data) | [microsoft/wavlm-base-plus](https://huggingface.co/microsoft/wavlm-base-plus)| Speech | MLS English + Internal data |
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| [xcodec-hubert-general](https://huggingface.co/hf-audio/xcodec-hubert-general) | [ZhenYe234/hubert_base_general_audio](https://huggingface.co/ZhenYe234/hubert_base_general_audio) | General audio | 200k hours internal data |
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| Model checkpoint | Semantic Model | Domain | Training Data |
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|--------------------------------------------|-----------------------------------------------------------------------|---------------|-------------------------------|
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| **[xcodec-hubert-librispeech](https://huggingface.co/hf-audio/xcodec-hubert-librispeech) (this model)** | [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) | Speech | Librispeech |
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| [xcodec-wavlm-mls](https://huggingface.co/hf-audio/xcodec-wavlm-mls) | [microsoft/wavlm-base-plus](https://huggingface.co/microsoft/wavlm-base-plus)| Speech | MLS English |
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| [xcodec-wavlm-more-data](https://huggingface.co/hf-audio/xcodec-wavlm-more-data) | [microsoft/wavlm-base-plus](https://huggingface.co/microsoft/wavlm-base-plus)| Speech | MLS English + Internal data |
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| [xcodec-hubert-general](https://huggingface.co/hf-audio/xcodec-hubert-general) | [ZhenYe234/hubert_base_general_audio](https://huggingface.co/ZhenYe234/hubert_base_general_audio) | General audio | 200k hours internal data |
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