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R910
/
Sanskrit_TTS_v2

Text-to-Speech
Transformers
Safetensors
English
Sanskrit
tts
sanskrit
audio-generation
text-generation-inference
unsloth
llama
trl
fine-tuned
devanagari
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use R910/Sanskrit_TTS_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use R910/Sanskrit_TTS_v2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-to-speech", model="R910/Sanskrit_TTS_v2")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("R910/Sanskrit_TTS_v2", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Unsloth Studio new

    How to use R910/Sanskrit_TTS_v2 with Unsloth Studio:

    Install Unsloth Studio (macOS, Linux, WSL)
    curl -fsSL https://unsloth.ai/install.sh | sh
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for R910/Sanskrit_TTS_v2 to start chatting
    Install Unsloth Studio (Windows)
    irm https://unsloth.ai/install.ps1 | iex
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for R910/Sanskrit_TTS_v2 to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for R910/Sanskrit_TTS_v2 to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="R910/Sanskrit_TTS_v2",
        max_seq_length=2048,
    )
Sanskrit_TTS_v2
418 MB
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  • 1 contributor
History: 7 commits
R910's picture
R910
Rename Readme.md to README.md
8102e34 verified 3 months ago
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  • tokenizer_config.json
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