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Add readme for github

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- ---
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- title: Music Descriptor
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- emoji: 🚀
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- colorFrom: blue
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- colorTo: indigo
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- sdk: gradio
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- sdk_version: 3.29.0
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- app_file: app.py
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- pinned: true
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- license: cc-by-nc-4.0
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- ---
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- <!-- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference -->
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- # Demo Introduction
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- This is an example of using the [MERT-v1-95M](https://huggingface.co/m-a-p/MERT-v1-95M) model as backbone to conduct multiple music understanding tasks with the universal represenation.
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- The tasks include EMO, GS, MTGInstrument, MTGGenre, MTGTop50, MTGMood, NSynthI, NSynthP, VocalSetS, VocalSetT.
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- More models can be referred at the [map organization page](https://huggingface.co/m-a-p).
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-
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- # Known Issues
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-
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- ## Audio Format Support
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- Theorectically, all the audio formats supported by [torchaudio.load()](https://pytorch.org/audio/stable/torchaudio.html#torchaudio.load) can be used in the demo. Theese should include but not limited to `WAV, AMB, MP3, FLAC`.
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- ## Error Output
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- Due the **hardware limitation** of the machine hosting our demospecification (2 CPU and 16GB RAM), there might be `Error` output when uploading long audios.
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- Unfortunately, we couldn't fix this in a short time since our team are all volunteer researchers.
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- We recommend to test audios less than 30 seconds or using the live mode if you are trying the [Music Descriptor demo](https://huggingface.co/spaces/m-a-p/Music-Descriptor) hosted online at HuggingFace Space.
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- This issue is expected to solve in the future by applying more community-support GPU resources or using other audio encoding strategy.
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- In the current stage, if you want to directly run the demo with longer audios, you could:
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- * clone this space `git clone https://huggingface.co/spaces/m-a-p/Music-Descriptor` and deploy the demo on your own machine with higher performance following the [official instruction](https://huggingface.co/docs/hub/spaces). The code will automatically use GPU for inference if there is GPU that can be detected by `torch.cuda.is_available()`.
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- * develop your own application with the MERT models if you have the experience of machine learning.
 
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+ This is a fork of the huggingface spaces for music description.
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+ Licenced under CC-BY-NC.
 
 
 
 
 
 
 
 
 
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+ I pulled it in here to work with this on a google colab.
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+ Check the original space at https://huggingface.co/spaces/m-a-p/Music-Descriptor