Instructions to use espnet/amuse_encodec_16k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use espnet/amuse_encodec_16k with ESPnet:
unknown model type (must be text-to-speech or automatic-speech-recognition)
- Notebooks
- Google Colab
- Kaggle
Download meta.yaml from espnet/amuse_encodec_16k: direct link, hf CLI and curl.
- Browser
- Download file 288 Bytes
-
https://huggingface.co/espnet/amuse_encodec_16k/resolve/main/meta.yaml
- Command line
-
hf download hf://espnet/amuse_encodec_16k/meta.yaml
-
curl -L -o meta.yaml https://huggingface.co/espnet/amuse_encodec_16k/resolve/main/meta.yaml
288 Bytes
| espnet: '202402' | |
| files: | |
| model_file: exp_16k/codec_train_encodec_fs16000_raw_fs16000/120epoch.pth | |
| python: 3.10.14 (main, May 6 2024, 19:42:50) [GCC 11.2.0] | |
| timestamp: 1718989440.461855 | |
| torch: 2.0.1 | |
| yaml_files: | |
| train_config: exp_16k/codec_train_encodec_fs16000_raw_fs16000/config.yaml | |