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RetentionLabs
/
personaplex-ko-ext-base

Moshi
Safetensors
Korean
personaplex
speech
full-duplex
korean
Model card Files Files and versions
xet
Community

Instructions to use RetentionLabs/personaplex-ko-ext-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Moshi

    How to use RetentionLabs/personaplex-ko-ext-base with Moshi:

    # pip install moshi
    # Run the interactive web server
    python -m moshi.server --hf-repo "RetentionLabs/personaplex-ko-ext-base"
    # Then open https://localhost:8998 in your browser
    # pip install moshi
    import torch
    from moshi.models import loaders
    
    # Load checkpoint info from HuggingFace
    checkpoint = loaders.CheckpointInfo.from_hf_repo("RetentionLabs/personaplex-ko-ext-base")
    
    # Load the Mimi audio codec
    mimi = checkpoint.get_mimi(device="cuda")
    mimi.set_num_codebooks(8)
    
    # Encode audio (24kHz, mono)
    wav = torch.randn(1, 1, 24000 * 10)  # [batch, channels, samples]
    with torch.no_grad():
        codes = mimi.encode(wav.cuda())
        decoded = mimi.decode(codes)
  • Notebooks
  • Google Colab
  • Kaggle
personaplex-ko-ext-base
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
RetentionLabs's picture
RetentionLabs
Korean finetune campaign weights (see README)
6d0093b verified 4 days ago
  • .gitattributes
    1.52 kB
    initial commit 4 days ago
  • README.md
    1.44 kB
    Korean finetune campaign weights (see README) 4 days ago
  • config.json
    2.58 kB
    Korean finetune campaign weights (see README) 4 days ago
  • extension.json
    19.6 kB
    Korean finetune campaign weights (see README) 4 days ago
  • generation_config.json
    44 Bytes
    Korean finetune campaign weights (see README) 4 days ago
  • model.safetensors
    16.8 GB
    xet
    Korean finetune campaign weights (see README) 4 days ago
  • tokenizer_spm_ko.model
    578 kB
    xet
    Korean finetune campaign weights (see README) 4 days ago