Instructions to use espnet/owsm_v4_base_102M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use espnet/owsm_v4_base_102M with ESPnet:
from espnet2.bin.asr_inference import Speech2Text model = Speech2Text.from_pretrained( "espnet/owsm_v4_base_102M" ) speech, rate = soundfile.read("speech.wav") text, *_ = model(speech)[0] - Notebooks
- Google Colab
- Kaggle
| espnet: '202412' | |
| files: | |
| s2t_model_file: exp/s2t_train_conv2d8_size384_e6_d6_mel128_raw_bpe50000/valid.total_count.ave_5best.pth | |
| python: 3.10.13 | packaged by conda-forge | (main, Dec 23 2023, 15:26:55) [GCC 12.3.0] | |
| timestamp: 1738818877.327384 | |
| torch: 2.5.1 | |
| yaml_files: | |
| s2t_train_config: exp/s2t_train_conv2d8_size384_e6_d6_mel128_raw_bpe50000/config.yaml | |