Pretrained models

Asteroid provides pretrained models through Hugging Face’s Model Hub. Have a look at this page to choose which model you want to use.

Enjoy having pretrained models? Please share your models if you train some :pray: It’s really simple with the Hub, check the next sections.

Using them

Loading a pretrained model is super simple!

from asteroid.models import ConvTasNet
model = ConvTasNet.from_pretrained('mpariente/ConvTasNet_WHAM!_sepclean')

You can also load it with Hub

from torch import hub
model = hub.load('mpariente/asteroid', 'conv_tasnet', 'mpariente/ConvTasNet_WHAM!_sepclean')

Model caching

When using a from_pretrained method, the model is downloaded and cached. The cache directory is either the value in the $ASTEROID_CACHE environment variable, or ~/.cache/torch/asteroid.

Share your models

At the end of each sharing-enabled recipe, all the necessary infos are gathered into a file, the only thing that’s left to is to add it to the Model Hub. After creating an account (here), you can

• Add a new model here. with a name like {model_name}_{dataset_name}_{task}_{sampling_rate}.

• Clone the repo (git clone the_URL_youre_at), cd into it.

• Copy the model_card_template.md and fill in the missing information.

• Move the pretrained model in the folder, rename it pytorch.bin.

• Register files and commit git add . && git commit -m "Model release: v1".

• And push :tada: git push :tada:

• Thank you! :pray:

You can have a look at the docs for more details!

Note about licenses

All Asteroid’s pretrained models are shared under the Attribution-ShareAlike 3.0 (CC BY-SA 3.0) license. This means that models are released under the same license as the original training data. If any non-commercial data is used during training (wsj0, WHAM’s noises etc..), the models are non-commercial use only. This is indicated in the bottom of the model page (ex: here on the bottom).