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encodecmae-base
lpepino/encodecmae-base
encodecmae-base is a machine learning model from lpepino. 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.
This is EnCodecMAE, an audio feature extractor pretrained with masked language modelling to predict discrete targets generated by EnCodec, a neural audio codec. For more details about the architecture and pretraining…
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Updated Jan 23, 2024
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At a glance
- License
- mit
- Access
- Public
- Created
- Sep 8, 2023
- Updated
- Jan 23, 2024
- SHA
- c3323187
Model card
From the Hugging Face model README
Model description
This is EnCodecMAE, an audio feature extractor pretrained with masked language modelling to predict discrete targets generated by EnCodec, a neural audio codec. For more details about the architecture and pretraining procedure, read the paper.
Usage
1) Clone the EnCodecMAE library:
git clone https://github.com/habla-liaa/encodecmae.git
2) Install it:
cd encodecmae
pip install -e .
3) Extract embeddings in Python:
from encodecmae import load_model
model = load_model('base', device='cuda:0')
features = model.extract_features_from_file('gsc/bed/00176480_nohash_0.wav')
- License
- mit
- Created
- Sep 8, 2023
- Updated
- Jan 23, 2024