Instructions to use espnet/owsm_v3.1_ebf_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use espnet/owsm_v3.1_ebf_base with ESPnet:
from espnet2.bin.asr_inference import Speech2Text model = Speech2Text.from_pretrained( "espnet/owsm_v3.1_ebf_base" ) speech, rate = soundfile.read("speech.wav") text, *_ = model(speech)[0] - Notebooks
- Google Colab
- Kaggle
| espnet: '202308' | |
| files: | |
| s2t_model_file: exp/s2t_train_s2t_ebf_conv2d_size384_e6_d6_piecewise_lr1e-3_warmup60k_flashattn_lessreg_raw_bpe50000/valid.total_count.ave_5best.pth | |
| python: 3.10.10 (main, Mar 21 2023, 18:45:11) [GCC 11.2.0] | |
| timestamp: 1705960184.857766 | |
| torch: 1.13.1 | |
| yaml_files: | |
| s2t_train_config: exp/s2t_train_s2t_ebf_conv2d_size384_e6_d6_piecewise_lr1e-3_warmup60k_flashattn_lessreg_raw_bpe50000/config.yaml | |