Hindi TTS — distilled IndicF5 student (~190M)
A distilled IndicF5 "student" (DiT depth-12 flow-matching, ~190M params) for Hindi
text-to-speech, plus a Vocos mel→waveform vocoder (24 kHz). Voice-cloning: it speaks
in the bundled reference voice (ref_audio.wav + ref_text.txt).
Live demo: https://huggingface.co/spaces/5ivatej/hindi-tts-190M
Files
| File | Description |
|---|---|
model.pt |
distilled d12 student weights (fp32, EMA) |
mel_basis.pt |
fixed mel filterbank (matches training) |
vocab.txt |
IndicF5 character vocab (2545 tokens) |
vocos/ |
Vocos vocoder (config.yaml + pytorch_model.bin) |
ref_audio.wav, ref_text.txt |
reference voice + its transcript |
Usage
The inference code lives in the demo Space repo. Point it at this model repo (default) and it downloads the weights automatically:
from infer_core import HindiTTS # from the Space repo
import soundfile as sf
tts = HindiTTS() # pulls weights from this repo on first run
sr, wave = tts.synth("नमस्ते, यह एक परीक्षण है।")
sf.write("out.wav", wave, sr)
License
Released under the MIT License. Note this model is derived from IndicF5 / F5-TTS — please also review and respect the upstream model and code licenses for your use case.
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