IndicF5 Kannada Bedtime

How to Use

from transformers import AutoModel
import soundfile as sf

model = AutoModel.from_pretrained(
    "mitvho09/IndicF5-Kannada-Bedtime",
    trust_remote_code=True,
)

audio = model(
    "ಮಕ್ಕಳೇ, ನಿದ್ರೆ ಮಾಡಿ.",
    ref_audio_path="reference.wav",
    ref_text="transcript of reference",
)

sf.write("output.wav", audio, 24000)

Evaluation

Compare stock vs fine-tuned audio in the comparison/ directory.

Fine-Tuning Details

This is an experimental fine-tune for the DreamVoice competition badge. Stock IndicF5 may perform better for general Kannada TTS.

--- language: kn tags: - text-to-speech - kannada - indicf5 - bedtime-stories base_model: ai4bharat/IndicF5 library_name: transformers license: mit --- # IndicF5 Kannada Bedtime Story Fine-Tune Fine-tuned [ai4bharat/IndicF5](https://huggingface.co/ai4bharat/IndicF5) on Kannada bedtime-story speech. ## Training Details - **Base model**: ai4bharat/IndicF5 (0.4B params) - **Training data**: Rasa Kannada (18 clips, ~2min) - **Training steps**: 300 - **Learning rate**: 1e-5 - **Final loss**: 0.4553 - **GPU**: A100-80GB (Modal) ## How to Use ```python from transformers import AutoModel import soundfile as sf model = AutoModel.from_pretrained( "mitvho09/IndicF5-Kannada-Bedtime", trust_remote_code=True, ) audio = model( "ಮಕ್ಕಳೇ, ನಿದ್ರೆ ಮಾಡಿ.", ref_audio_path="reference.wav", ref_text="transcript of reference", ) sf.write("output.wav", audio, 24000) ``` ## Evaluation Compare stock vs fine-tuned audio in the `comparison/` directory. ## Fine-Tuning Details This is an experimental fine-tune for the DreamVoice competition badge. Stock IndicF5 may perform better for general Kannada TTS.