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WavLM_models_for_fairseq_finetuning
wyz/WavLM_models_for_fairseq_finetuning
WavLM_models_for_fairseq_finetuning is a machine learning model from wyz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
The provided checkpoints are adapated from the official WavLM models released at https://github.com/microsoft/unilm/blob/master/wavlm/README.mdpre-trained-models to be used for fine-tuning in fairseq.
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Updated Jun 7, 2023
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At a glance
- License
- mit
- Access
- Public
- Created
- Jun 7, 2023
- Updated
- Jun 7, 2023
- SHA
- e8da9a07
Model card
From the Hugging Face model README
Note
The provided checkpoints are adapated from the official WavLM models released at https://github.com/microsoft/unilm/blob/master/wavlm/README.md#pre-trained-models to be used for fine-tuning in fairseq.
They should be used together with the specialized fairseq repository https://github.com/Emrys365/fairseq/tree/wavlm where the support for WavLM is added.
NOTE: The adapted checkpoints are only guaranteed to have the same
model configurationandmodel parametersas the official released models. The other parameters (such astask hyperparametersandoptimizer hyperparameters) are just a template.Therefore, these adapted checkpoints are only suitable to be used as an initialization for fine-tuning in the downstream tasks, NOT for continuing pre-training.
Please refer to https://github.com/Emrys365/fairseq/blob/wavlm/examples/wavlm/README.md#load-adapted-checkpoints-for-fairseq-finetuning for more information.
- License
- mit
- Created
- Jun 7, 2023
- Updated
- Jun 7, 2023