Update README.md

README.md

@@ -11,7 +11,7 @@ license: mit
 This repository is a wrapper around the original **Descript Audio Codec** model, a high fidelity general neural audio codec, introduced in the paper titled **High-Fidelity Audio Compression with Improved RVQGAN**.
 
 It is designed to be used as a drop-in replacement of the [transformers implementation](https://huggingface.co/docs/transformers/v4.39.3/en/model_doc/encodec#overview) of [Encodec](https://github.com/facebookresearch/encodec), so that architectures that use Encodec can also be trained with DAC instead.
-The [Parler-TTS library](https://github.com/huggingface/parler-tts) is an example of how to use DAC to train high-quality TTS models. We released [Parler-TTS Mini v0.1]("https://huggingface.co/parler-tts/parler_tts_300M_v0.1"), a first iteration model trained using 10k hours of narrated audiobooks. It generates high-quality speech with features that can be controlled using a simple text prompt (e.g. gender, background noise, speaking rate, pitch and reverberation)
+The [Parler-TTS library](https://github.com/huggingface/parler-tts) is an example of how to use DAC to train high-quality TTS models. We released [Parler-TTS Mini v0.1]("https://huggingface.co/parler-tts/parler_tts_mini_v0.1"), a first iteration model trained using 10k hours of narrated audiobooks. It generates high-quality speech with features that can be controlled using a simple text prompt (e.g. gender, background noise, speaking rate, pitch and reverberation)
 
 To use this checkpoint, you first need to install the [Parler-TTS library](https://github.com/huggingface/parler-tts) with (to do once):
 ```sh