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AutoArk-AI
/
GPA

Text-to-Speech
Transformers
ONNX
Safetensors
English
Chinese
qwen3
text-generation
automatic-speech-recognition
voice-conversion
speech
audio
custom_code
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use AutoArk-AI/GPA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AutoArk-AI/GPA with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-to-speech", model="AutoArk-AI/GPA", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("AutoArk-AI/GPA", trust_remote_code=True)
    model = AutoModelForCausalLM.from_pretrained("AutoArk-AI/GPA", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
GPA / BiCodec
1.9 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
chua's picture
chua
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435ac83 verified 4 months ago
  • wav2vec2-large-xlsr-53
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  • README.md
    2.29 kB
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  • config.json
    1.77 kB
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  • config.yaml
    1.33 kB
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  • model.safetensors
    626 MB
    xet
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  • preprocessor_config.json
    212 Bytes
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