Add library name and links

This PR adds the `library_name` to the metadata, specifying that this model uses the Diffusers library. It also adds links to the project page and the Github repository for easier access to the project details and code.

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).