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kenpath
/
svara-tts-v1

Text-to-Speech
Transformers
Safetensors
GGUF
llama
text-generation
speech-synthesis
multilingual
indic
orpheus
lora
low-latency
zero-shot
emotions
discrete-audio-tokens
text-generation-inference
Model card Files Files and versions
xet
Community
2

Instructions to use kenpath/svara-tts-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use kenpath/svara-tts-v1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-to-speech", model="kenpath/svara-tts-v1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("kenpath/svara-tts-v1")
    model = AutoModelForCausalLM.from_pretrained("kenpath/svara-tts-v1")
  • Notebooks
  • Google Colab
  • Kaggle
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Free studio vocal data for Svara TTS community benchmarking

#1 opened 25 days ago by
MachineAI87
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