---
license: mit
base_model: sarvamai/sarvam-1
library_name: peft
pipeline_tag: text-generation
tags:
  - grapheme-to-phoneme
  - g2p
  - tts
  - code-mixed
  - hinglish
  - lora
  - peft
language:
  - hi
  - en
---

# Sarvam-1 — Hinglish Grapheme-to-Phoneme (G2P) LoRA

A LoRA adapter for [`sarvamai/sarvam-1`](https://huggingface.co/sarvamai/sarvam-1)
(2B) that performs **Grapheme-to-Phoneme (G2P)** on normalized code-mixed
Hindi/English text, emitting **IPA**. It is distilled from
[`espeak-ng`](https://github.com/espeak-ng/espeak-ng): a single LLM thus does
**both** text-normalization (see the companion
[TN adapter](https://huggingface.co/AK04-IXR/sarvam1-hinglish-tn-lora))
and phonemization — a unified TTS front-end.

Part of **[fast-indic-tts](https://github.com/Abhijit89Kumar/fast-indic-tts)**.

> **Live demo:** https://huggingface.co/spaces/AK04-IXR/fast-indic-tts


## Results
On a held-out split it reproduces the espeak-ng reference with **0.00% PER /
100% exact phoneme match** (n=60) — i.e. it generalizes the phonemizer's
deterministic mapping to unseen sentences.

## Usage
```python
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

tok = AutoTokenizer.from_pretrained("sarvamai/sarvam-1")
m = AutoModelForCausalLM.from_pretrained("sarvamai/sarvam-1")
m = PeftModel.from_pretrained(m, "AK04-IXR/sarvam1-hinglish-g2p-lora")

prompt = "Input: Mera flight ticket pee-en-aar eight three nine two hai.\nOutput:"
ids = tok(prompt, return_tensors="pt").to(m.device)
out = m.generate(**ids, max_new_tokens=160, do_sample=False)
print(tok.decode(out[0][ids['input_ids'].shape[1]:], skip_special_tokens=True))
```

## Training
LoRA (r=16, α=32; 0.94% of params) on ~7k (text → IPA) pairs phonemized by
espeak-ng (en-us), 3 epochs, bf16, single A100.

## Limitations
Distilled from espeak-ng, so it *matches* (does not surpass) that reference;
trained on Latin-script normalized text (Devanagari-carrier lines held out), and
code-switched phonemization (per-span language ID) remains an open problem.