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UBC-NLP
/
Simba-TTS-lin

Automatic Speech Recognition
Transformers
Safetensors
Lingala
vits
text-to-audio
audio
speech
african-languages
multilingual
simba
low-resource
speech-recognition
asr
Model card Files Files and versions
xet
Community

Instructions to use UBC-NLP/Simba-TTS-lin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use UBC-NLP/Simba-TTS-lin with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="UBC-NLP/Simba-TTS-lin")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTextToWaveform
    
    tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/Simba-TTS-lin")
    model = AutoModelForTextToWaveform.from_pretrained("UBC-NLP/Simba-TTS-lin")
  • Notebooks
  • Google Colab
  • Kaggle
Simba-TTS-lin
145 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 11 commits
elmadany's picture
elmadany
Update README.md
f12042b verified 3 months ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    5.32 kB
    Update README.md 3 months ago
  • added_tokens.json
    18 Bytes
    Upload tokenizer about 1 year ago
  • config.json
    2.03 kB
    Upload model 12 months ago
  • model.safetensors
    145 MB
    xet
    Upload model 12 months ago
  • preprocessor_config.json
    254 Bytes
    Upload feature extractor about 1 year ago
  • special_tokens_map.json
    275 Bytes
    Upload tokenizer 12 months ago
  • tokenizer_config.json
    670 Bytes
    Upload tokenizer 12 months ago
  • vocab.json
    423 Bytes
    Upload tokenizer about 1 year ago