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Update README.md

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- ---
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- license: mit
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- tags:
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- - audiocraft
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- base_model: facebook/musicgen-small
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- ---
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  small model trained on 295 freely available drum breaks. No text conditioning was used (inspired by https://github.com/aaronabebe/micro-musicgen).
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  useful docs: https://github.com/facebookresearch/audiocraft/blob/main/docs/TRAINING.md
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  ```
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  dora run solver=musicgen/musicgen_base_32khz model/lm/model_scale=small conditioner=none dataset.batch_size=5 dset=audio/breaks.yaml dataset.valid.num_samples=1 generate.every=10000 evaluate.every=10000 optim.optimizer=adamw optim.lr=1e-4 optim.adam.weight_decay=0.01 checkpoint.save_every=5
 
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+ ---
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+ license: mit
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+ tags:
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+ - audiocraft
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+ base_model: facebook/musicgen-small
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+ ---
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  small model trained on 295 freely available drum breaks. No text conditioning was used (inspired by https://github.com/aaronabebe/micro-musicgen).
 
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  useful docs: https://github.com/facebookresearch/audiocraft/blob/main/docs/TRAINING.md
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+ examples:
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+ (picked at random)
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+
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+ <table style="width:100%; text-align:center;">
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+ <tr>
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+ <td>
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+ <audio controls>
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+ <source src="https://huggingface.co/mateo-19182/all-the-breaks/resolve/main/3.wav?download=true" type="audio/wav">
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+ Your browser does not support the audio element.
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+ </audio>
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+ </td>
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+ <td>
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+ <audio controls>
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+ <source src="https://huggingface.co/mateo-19182/all-the-breaks/resolve/main/sample_3.wav?download=true" type="audio/wav">
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+ Your browser does not support the audio element.
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+ </audio>
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+ </td>
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+ </tr>
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+ <tr>
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+ <td>
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+ <audio controls>
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+ <source src="https://huggingface.co/mateo-19182/all-the-breaks/resolve/main/9.wav?download=true" type="audio/wav">
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+ Your browser does not support the audio element.
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+ </audio>
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+ </td>
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+ <td>
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+ <audio controls>
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+ <source src="https://huggingface.co/mateo-19182/all-the-breaks/resolve/main/sample_9.wav?download=true" type="audio/wav">
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+ Your browser does not support the audio element.
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+ </audio>
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+ </td>
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+ </tr>
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+ </table>
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+
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+
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  ```
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  dora run solver=musicgen/musicgen_base_32khz model/lm/model_scale=small conditioner=none dataset.batch_size=5 dset=audio/breaks.yaml dataset.valid.num_samples=1 generate.every=10000 evaluate.every=10000 optim.optimizer=adamw optim.lr=1e-4 optim.adam.weight_decay=0.01 checkpoint.save_every=5