Checkpoints

There are two main ways to load pretrained checkpoints in NeMo:

• Using the restore_from() method to load a local checkpoint file (.nemo), or

• Using the from_pretrained() method to download and set up a checkpoint from the cloud.

Note that these instructions are for loading fully trained checkpoints for evaluation or fine-tuning. For resuming an unfinished training experiment, use the Experiment Manager to do so by setting the resume_if_exists flag to True.

Local Checkpoints

• Save Model Checkpoints: NeMo automatically saves final model checkpoints with .nemo suffix. You could also manually save any model checkpoint using model.save_to(<checkpoint_path>.nemo).

• Load Model Checkpoints: if you’d like to load a checkpoint saved at <path/to/checkpoint/file.nemo>, use the restore_from() method below, where <MODEL_BASE_CLASS> is the model class of the original checkpoint.

import nemo.collections.audio as nemo_audio
model = nemo_audio.models.<MODEL_BASE_CLASS>.restore_from(restore_path="<path/to/checkpoint/file.nemo>")

Pretrained Checkpoints

The table below in Audio Models list part of available pre-trained audio processing models including speech processing, restoration and extraction.

Load Model Checkpoints

The models can be accessed via the from_pretrained() method inside the audio model class. In general, you can load any of these models with code in the following format,

import nemo.collections.audio as nemo_audio
model = nemo_audio.models.<MODEL_BASE_CLASS>.from_pretrained(model_name="<MODEL_NAME>")

where <MODEL_NAME> is the value in Model Name column in the tables in Audio Models. These names are predefined in the each model’s member function self.list_available_models().

Audio Models

Speech Enhancement Models

Model Name	Dataset	Sampling Rate	Model Class	Model Card
nvidia/se_den_sb_16k_small	WSJ0+CHiME	16000Hz	nemo.collections.audio.models.SchroedingerBridgeAudioToAudioModel	se_den_sb_16k_small
nvidia/se_der_sb_16k_small	WSJ0+Reverb	16000Hz	nemo.collections.audio.models.SchroedingerBridgeAudioToAudioModel	se_der_sb_16k_small

SSL Models

Model Name	Dataset	Sampling Rate	Model Class	Model Card
nvidia/sr_ssl_flowmatching_16k_430m	Libri-Light	16000Hz	nemo.collections.audio.models.FlowMatchingAudioToAudioModel	sr_ssl_flowmatching_16k_430m