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README.md

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 # Hybrid-MAGNeT - Small - 300M
 
-Hybrid-MAGNeT is a text-to-music and text-to-sound model capable of generating high-quality audio samples conditioned on text descriptions.
-It is a mixture between autoregressive and masked generative non-autoregressive Transformers trained over a 32kHz EnCodec tokenizer with 4 codebooks sampled at 50 Hz. 
+MAGNeT is a text-to-music and text-to-sound model capable of generating high-quality audio samples conditioned on text descriptions.
+Hybrid-MAGNeT is a mixture between autoregressive and masked generative non-autoregressive Transformers trained over a 32kHz EnCodec tokenizer with 4 codebooks sampled at 50 Hz. 
 Hybrid-MAGNeT generates 30-second long music samples.
 
 MAGNeT was published in [Masked Audio Generation using a Single Non-Autoregressive Transformer](https://arxiv.org/abs/2401.04577) by *Alon Ziv, Itai Gat, Gael Le Lan, Tal Remez, Felix Kreuk, Alexandre Défossez, Jade Copet, Gabriel Synnaeve, Yossi Adi*.