from espnet3.publication import InferenceModel
model = InferenceModel.from_pretrained("espnet/meld_esp2_cls_wavlm_base_plus", trust_user_code=True)
result = model(sample)
Packaging
Bundle:
model_pack
Exp dir:
./exp/train_cls_wavlm_transformer
Strategy:
copy experiment outputs; include extra recipe assets; apply exclude filters
@inproceedings{watanabe2018espnet,
author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and
Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner
and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
title={{ESPnet}: End-to-End Speech Processing Toolkit},
year={2018},
booktitle={Proceedings of Interspeech},
pages={2207--2211},
doi={10.21437/Interspeech.2018-1456}
}
Runs of espnet meld_esp2_cls_wavlm_base_plus on huggingface.co
28
Total runs
0
24-hour runs
7
3-day runs
12
7-day runs
28
30-day runs
More Information About meld_esp2_cls_wavlm_base_plus huggingface.co Model
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