PyTorch
music
text-to-music
symbolic-music
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@@ -70,11 +70,18 @@ generated_midi.dump_midi("output.mid")
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  ```
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  ## Installation
 
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  ```bash
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  git clone https://github.com/AMAAI-Lab/text-2-midi
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  cd text-2-midi
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  pip install -r requirements.txt
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  ```
 
 
 
 
 
 
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  ## Datasets
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  The MidiCaps dataset is a large-scale dataset of 168k MIDI files paired with rich text captions. These captions contain musical attributes such as key, tempo, style, and mood, making it ideal for text-to-MIDI generation tasks.
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  | Metric | text2midi | MidiCaps | MuseCoco |
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  |---------------------|-----------|----------|----------|
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- | CR ↑ | 2.14 | 3.43 | 2.12 |
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  | CLAP ↑ | 0.22 | 0.26 | 0.21 |
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- | TB (%) ↑ | 27.85 | - | 21.71 |
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- | TBT (%) ↑ | 57.78 | - | 54.63 |
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- | CK (%) ↑ | 7.69 | - | 13.70 |
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- | CKD (%) ↑ | 14.80 | - | 14.59 |
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  **Note**:
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  CR = Compression ratio
@@ -132,6 +139,12 @@ accelerate launch train.py \
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  --epochs=40 \
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  ```
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  ## Citation
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  If you use text2midi in your research, please cite:
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  ```
@@ -142,3 +155,4 @@ If you use text2midi in your research, please cite:
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  year={2025}
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  }
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  ```
 
 
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  ```
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  ## Installation
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+ If you have CUDA supported machine:
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  ```bash
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  git clone https://github.com/AMAAI-Lab/text-2-midi
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  cd text-2-midi
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  pip install -r requirements.txt
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  ```
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+ Alternatively, if you have MPS supported machine:
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+ ```bash
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+ git clone https://github.com/AMAAI-Lab/text-2-midi
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+ cd text-2-midi
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+ pip install -r requirements-mac.txt
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+ ```
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  ## Datasets
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  The MidiCaps dataset is a large-scale dataset of 168k MIDI files paired with rich text captions. These captions contain musical attributes such as key, tempo, style, and mood, making it ideal for text-to-MIDI generation tasks.
 
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  | Metric | text2midi | MidiCaps | MuseCoco |
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  |---------------------|-----------|----------|----------|
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+ | CR ↑ | 2.31 | 3.43 | 2.12 |
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  | CLAP ↑ | 0.22 | 0.26 | 0.21 |
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+ | TB (%) ↑ | 39.70 | - | 21.71 |
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+ | TBT (%) ↑ | 65.80 | - | 54.63 |
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+ | CK (%) ↑ | 33.60 | - | 13.70 |
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+ | CKD (%) ↑ | 35.60 | - | 14.59 |
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  **Note**:
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  CR = Compression ratio
 
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  --epochs=40 \
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  ```
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+ ## Inference
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+ We spport inference on CUDA, MPS and cpu. Please make sure you have pip installed the correct requirement file (requirments.txt for CUDA, requirements-mac.txt for MPS)
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+ ```bash
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+ python model/transformer_model.py --caption <your intended descriptions>
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+ ```
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+
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  ## Citation
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  If you use text2midi in your research, please cite:
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  ```
 
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  year={2025}
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  }
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  ```
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+