File size: 1,673 Bytes
0ff9d37 0b704d8 0ff9d37 0b704d8 0ff9d37 0b704d8 0ff9d37 0b704d8 0ff9d37 0b704d8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | ---
license: other
license_name: per-codec
license_link: https://huggingface.co/BricksDisplay/codec.cpp-gguf#license
tags:
- codec.cpp
- gguf
- audio
- neural-audio-codec
---
# codec.cpp GGUFs
Neural audio codecs for [codec.cpp](https://github.com/mybigday/codec.cpp): turn
speech into discrete tokens and back, offline on CPU or GPU.
| Codec | Sample rate | Token rate | Files |
|---|---|---|---|
| [IBM DAC.speech v1.0](https://huggingface.co/ibm-research/DAC.speech.v1.0) | 24 kHz | 75 frames/s | `ibm-research--DAC.speech*.gguf` |
| [NVIDIA NeMo Nano Codec](https://huggingface.co/nvidia/nemo-nano-codec-22khz-0.6kbps-12.5fps) | 22.05 kHz | 12.5 frames/s (0.6 kbps) | `nemo-nano-codec-22khz-0.6kbps-12.5fps*.gguf` |
| [WavTokenizer large (speech)](https://huggingface.co/novateur/WavTokenizer-large-speech-75token) | 24 kHz | 75 tokens/s | `wavtokenizer-large-speech-75tokens*.gguf` |
Each codec comes in several precisions: the file without a suffix is F16
(recommended), `-F32` is full precision, `-Q8_0` / `-Q5_K_M` / `-Q4_K_M` are
smaller and faster at some quality cost.
## Run
```bash
hf download BricksDisplay/codec.cpp-gguf ibm-research--DAC.speech.gguf --local-dir codecs
./build/codec-cli encode --model codecs/ibm-research--DAC.speech.gguf --in speech.wav --out codes.npy
./build/codec-cli decode --model codecs/ibm-research--DAC.speech.gguf --codes codes.npy --out decoded.wav
```
Build instructions, GPU flags and the Python API are in the
[codec.cpp README](https://github.com/mybigday/codec.cpp).
## License
Each codec keeps its original license: DAC.speech CDLA-Permissive-2.0, NeMo Nano Codec the NVIDIA Open Model License, WavTokenizer MIT.
|