facebook/encodec_24khz
feature-extraction model by facebook
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This model card provides details and information about EnCodec, a state-of-the-art real-time audio codec developed by Meta AI. EnCodec is a high-fidelity audio codec leveraging neural networks. It introduces a streaming encoder-decoder architecture with quantized latent space, trained in an end-to-end fashion. The model simplifies and speeds up training using a single multiscale spectrogram adversary that efficiently reduces artifacts and produces high-quality samples. It also includes a novel loss balancer mechanism that stabilizes training by decoupling the choice of hyperparameters from the typical scale of the loss. Additionally, lightweight Transformer models are used to further compress the obtained representation while maintaining real-time performance. EnCodec can be used directly as an audio codec for real-time compression and decompression of audio signals. It provides high-quality audio compression and efficient decoding. The model was trained on various bandwiths, which can be specified when encoding (compressing) and decoding (decompressing). Two different setup exist for…
Read the full model card ↗ · Preview checked 2026-10-31T22:16:26.924Z
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- Model Card for EnCodec
- Model Details
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Model overview
facebook/encodec_24khz is a feature-extraction model repository published by facebook on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- feature-extraction
- Library
- transformers
- Recent downloads (30 days)
- 95,773
- Cumulative likes
- 57
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 23,273,218
- Architecture
- EncodecModel
- License
- Not reported — check the model card
- Access
- Not gated by Hugging Face
- Created
- 2023-06-12T16:10:36.000Z
- Last modified
- 2023-07-25T11:28:04.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-08T06:42:12.906Z. Daily imports are snapshots, not real-time monitoring.
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