Text-to-Audio
Audiocraft
magnet
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@@ -138,7 +138,7 @@ The model was trained on licensed data using the following sources: the [Meta Mu
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  Below are the objective metrics obtained on MusicCaps with the released model. Note that for the publicly released models, we had all the datasets go through a state-of-the-art music source separation method, namely using the open source [Hybrid Transformer for Music Source Separation](https://github.com/facebookresearch/demucs) (HT-Demucs), in order to keep only the instrumental part. This explains the difference in objective metrics with the models used in the paper.
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  | Model | Frechet Audio Distance | KLD | Text Consistency |
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  | **facebook/magnet-small-10secs** | 4.22 | 1.11 | 0.28 |
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  | facebook/magnet-medium-10secs | 4.61 | 1.14 | 0.28 |
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  | facebook/magnet-small-30secs | 4.35 | 1.17 | 0.28 |
 
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  Below are the objective metrics obtained on MusicCaps with the released model. Note that for the publicly released models, we had all the datasets go through a state-of-the-art music source separation method, namely using the open source [Hybrid Transformer for Music Source Separation](https://github.com/facebookresearch/demucs) (HT-Demucs), in order to keep only the instrumental part. This explains the difference in objective metrics with the models used in the paper.
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  | Model | Frechet Audio Distance | KLD | Text Consistency |
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+ |---|---|---|---|
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  | **facebook/magnet-small-10secs** | 4.22 | 1.11 | 0.28 |
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  | facebook/magnet-medium-10secs | 4.61 | 1.14 | 0.28 |
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  | facebook/magnet-small-30secs | 4.35 | 1.17 | 0.28 |