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sudoping01
/
bambara-tts

Text-to-Speech
Transformers
Safetensors
Bambara
vits
text-to-audio
mms
multilingual
Open-Source
Mali
Bambara
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use sudoping01/bambara-tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sudoping01/bambara-tts with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-to-speech", model="sudoping01/bambara-tts")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTextToWaveform
    
    tokenizer = AutoTokenizer.from_pretrained("sudoping01/bambara-tts")
    model = AutoModelForTextToWaveform.from_pretrained("sudoping01/bambara-tts")
  • Notebooks
  • Google Colab
  • Kaggle
bambara-tts
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
sudoping01's picture
sudoping01
Update README.md
0206e79 verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    2.26 kB
    Update README.md about 1 year ago
  • added_tokens.json
    18 Bytes
    Upload tokenizer about 1 year ago
  • config.json
    1.64 kB
    Upload model about 1 year ago
  • model.safetensors
    145 MB
    xet
    Upload model about 1 year ago
  • special_tokens_map.json
    47 Bytes
    Upload tokenizer about 1 year ago
  • tokenizer_config.json
    680 Bytes
    Upload tokenizer about 1 year ago
  • vocab.json
    395 Bytes
    Upload tokenizer about 1 year ago