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README.md
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---
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a prompt generator for the [ACE-Step](https://huggingface.co/ACE-Step/ACE-Step-v1-3.5B) music generation model, fintuned from the MuFun model proposed in [Advancing the Foundation Model for Music Understanding](https://arxiv.org/abs/2508.01178)
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## Usage
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some audio processing packages like mutagen, torchaudio are needed to be installed
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```python
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model = AutoModelForCausalLM.from_pretrained(hf_path, trust_remote_code=True, torch_dtype="bfloat16")
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model.to(device)
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aud="/path/to/your/song.
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inp='<audio>\nDeconstruct this song, listing its tags and lyrics. Directly output a JSON object with prompt and lyrics fields, without any additional explanations or text.'
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res=model.chat(prompt=inp, audio_files=aud, segs=None, tokenizer=tokenizer)
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print(res)
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---
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a prompt generator for the [ACE-Step](https://huggingface.co/ACE-Step/ACE-Step-v1-3.5B) music generation model, fintuned from the MuFun model proposed in [Advancing the Foundation Model for Music Understanding](https://arxiv.org/abs/2508.01178)
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train code: https://github.com/laitselec/MuFun
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## Usage
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some audio processing packages like mutagen, torchaudio are needed to be installed
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```python
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model = AutoModelForCausalLM.from_pretrained(hf_path, trust_remote_code=True, torch_dtype="bfloat16")
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model.to(device)
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aud="/path/to/your/song.wav"
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inp='<audio>\nDeconstruct this song, listing its tags and lyrics. Directly output a JSON object with prompt and lyrics fields, without any additional explanations or text.'
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res=model.chat(prompt=inp, audio_files=aud, segs=None, tokenizer=tokenizer)
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print(res)
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