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BricksDisplay
/
ellie-Bert-VITS2

Text-to-Speech
Transformers
ONNX
Safetensors
Chinese
bert_vits2
feature-extraction
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use BricksDisplay/ellie-Bert-VITS2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BricksDisplay/ellie-Bert-VITS2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-to-speech", model="BricksDisplay/ellie-Bert-VITS2", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("BricksDisplay/ellie-Bert-VITS2", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ellie-Bert-VITS2
3.51 GB
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  • 1 contributor
History: 30 commits
hans00's picture
hans00
Create processor_config.json
cdcafe3 verified about 1 year ago
  • bert_zh
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  • data
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  • onnx
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  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
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  • config.json
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  • configuration_bert_vits2.py
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  • model.safetensors
    1.59 GB
    xet
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  • modeling_bert_vits2.py
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  • preprocessor_config.json
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  • processing_bert_vits2.py
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  • processor_config.json
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  • special_tokens_map.json
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  • tokenization_bert_vits2.py
    8.68 kB
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  • tokenizer.json
    2.78 kB
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  • tokenizer_config.json
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  • vocab.json
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