

# 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 configuration` and `model parameters` as the official released models. The other parameters (such as `task hyperparameters` and `optimizer 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"}
license:mit region:us
TAGS
#license-mit #region-us 



# Note

The provided checkpoints are adapated from the official WavLM models released at URL to be used for fine-tuning in fairseq.

They should be used together with the specialized fairseq repository URL where the support for WavLM is added.

> NOTE: The adapted checkpoints are only guaranteed to have the same 'model configuration' and 'model parameters' as the official released models. The other parameters (such as 'task hyperparameters' and 'optimizer 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 URL for more information.

# Note

The provided checkpoints are adapated from the official WavLM models released at URL to be used for fine-tuning in fairseq.

They should be used together with the specialized fairseq repository URL where the support for WavLM is added.

> NOTE: The adapted checkpoints are only guaranteed to have the same 'model configuration' and 'model parameters' as the official released models. The other parameters (such as 'task hyperparameters' and 'optimizer 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 URL for more information.
TAGS
#license-mit #region-us 
 # Note

The provided checkpoints are adapated from the official WavLM models released at URL to be used for fine-tuning in fairseq.

They should be used together with the specialized fairseq repository URL where the support for WavLM is added.

> NOTE: The adapted checkpoints are only guaranteed to have the same 'model configuration' and 'model parameters' as the official released models. The other parameters (such as 'task hyperparameters' and 'optimizer 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 URL for more information.