Add library name and links (#2)

- Add library name and links (106b27de2fe0b158df5a2911eb4344a10200ca8f)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -1,25 +1,27 @@
 ---
-license: mit
-model_type: diffusers
-tags:
-- music
-- art
-- text-to-audio
-language:
-- en
 datasets:
 - seungheondoh/LP-MusicCaps-MSD
 - DynamicSuperb/MusicGenreClassification_FMA
 - DynamicSuperb/MARBLEMusicTagging_MagnaTagATune
 - agkphysics/AudioSet
+language:
+- en
+license: mit
 pipeline_tag: text-to-audio
+tags:
+- music
+- art
+- text-to-audio
+model_type: diffusers
+library_name: diffusers
 ---
 
 ## Model Description
 
-This model allows for easy setup and usage for generating music from text prompts.
+This model, QA-MDT, allows for easy setup and usage for generating music from text prompts. It incorporates a quality-aware training strategy to improve the fidelity of generated music.
 
 ## How to Use
 
-refer to : https://github.com/ivcylc/qa-mdt 
-with huggingface space
+A Hugging Face Diffusers implementation is available at [this model](https://huggingface.co/jadechoghari/openmusic) and [this space](https://huggingface.co/spaces/jadechoghari/OpenMusic). For more detailed instructions and the official PyTorch implementation, please refer to the project's [Github repository](https://github.com/ivcylc/qa-mdt) and [project page](https://qa-mdt.github.io/).
+
+The model was presented in the paper [QA-MDT: Quality-aware Masked Diffusion Transformer for Enhanced Music Generation](https://huggingface.co/papers/2405.15863).