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Sponsored by
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Respair / Higgs_Codec_Extended
Model's Last Updated: August 14 2025
Introduction of Higgs_Codec_Extended
Model Details of Higgs_Codec_Extended
This is an on-going project. it is a modified version of Higgs-Boson audio tokenizer, you can fully train it. all scripts have been tested. a Few notes however:
-
this is not backward compatible with the original checkpoint (I think you can tweak it to be, but you have to adhere to Boson community license if you do.)
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I highly recommend you to pretrain the model without the mel and adversarial setup first. it saves you a significant amount of compute, time and speed-up your convergence. raise the batch size as much as you can before the adversarial phase.
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for the semantic teacher, I am using
utter-project/mHuBERT-147which has a good multilingual support. if you want the original setup you can change it in the config. -
The loss weights and hyperparameters may not be ideal, feel free to play around with different values.
I will train a checkpoint on a larger enough dataset one of these days after figuring out a few things first. but the setup is solid.
Training
python train_boson_mixed_precision.py --data_csv "yourdata.csv" \ # full path to your audio files, the format can be anything .mp3 .wav .ogg etc.
--config config.json --batch_size 42 \
--use_mixed_precision \
--use_discriminator
Simple Inference
take a look at the notebook
Batch inference
take a look at boson_codeit.py
Happy using / training (
inshallah
).
Runs of Respair Higgs_Codec_Extended on huggingface.co
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More Information About Higgs_Codec_Extended huggingface.co Model
Url of Higgs_Codec_Extended
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Provider of Higgs_Codec_Extended huggingface.co
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Updated:June 30 2025
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