Instructions to use facebook/encodec_24khz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/encodec_24khz with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/encodec_24khz")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("facebook/encodec_24khz") model = AutoModel.from_pretrained("facebook/encodec_24khz", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -55,7 +55,8 @@ Use the following code to get started with the EnCodec model using a dummy examp
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pip install --upgrade pip
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pip install --upgrade
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```
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Then load an audio sample, and run a forward pass of the model:
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```
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pip install --upgrade pip
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pip install --upgrade datasets[audio]
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pip install git+https://github.com/huggingface/transformers.git@main
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```
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Then load an audio sample, and run a forward pass of the model:
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