---
license: mit
language:
- hi
pipeline_tag: text-to-speech
tags:
- text-to-speech
- hindi
- tts
- f5-tts
- indicf5
- flow-matching
---

# 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:

```python
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.