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telecomadm1145
/
Kiseki-TTS

Text-to-Speech
Transformers
TensorBoard
Safetensors
Japanese
mamba2_s2s
text2text-generation
automatic-speech-recognition
mamba2
state-space-model
japanese
neural-audio-codec
custom_code
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use telecomadm1145/Kiseki-TTS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use telecomadm1145/Kiseki-TTS with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-to-speech", model="telecomadm1145/Kiseki-TTS", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForSeq2SeqLM
    model = AutoModelForSeq2SeqLM.from_pretrained("telecomadm1145/Kiseki-TTS", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Kiseki-TTS
1.65 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 17 commits
telecomadm1145's picture
telecomadm1145
Update modeling_mamba2_s2s.py
ceb563a verified about 1 hour ago
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  • README.md
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  • config.json
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  • events.out.tfevents.1786788965.5a2360ff5259.58.0
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  • example_output.wav
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  • model.safetensors
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  • modeling_mamba2_s2s.py
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  • tokenizer.json
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  • tokenizer_config.json
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