---
license: mit
language:
- bn
metrics:
- wer
- cer
tags:
- seq2seq
- ipa
- bengali
- byt5
widget:
- text: "<Narail> আমি সে বাবুর মামু বাড়ি গিছিলাম।"
---


# Regional bengali text to IPA transcription - byT5-small

## A word of caution: the model is constantly being updated! You may see jumps in performance!

This is a fine-tuned version of the [google/byt5-small](https://huggingface.co/google/byt5-small) for the task of generating IPA transcriptions from regional bengali text. 
This was done on the dataset of the competition [“ভাষামূল: মুখের ভাষার খোঁজে“](https://www.kaggle.com/competitions/regipa/overview) by Bengali.AI.

Scores achieved till now (test scores):
- **Word error rate (wer)**: 0.01732
- **Char error rate (cer)**: 0.01491

Supported district tokens:
- Kishoreganj
- Narail
- Narsingdi
- Chittagong
- Rangpur
- Tangail


## Loading & using the model
```python
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("smji/ben2ipa-byt5small")
model = AutoModelForSeq2SeqLM.from_pretrained("smji/ben2ipa-byt5small")

"""
  The format of the input text MUST BE: <district> <bengali_text>
"""
text = "<district> bengali_text_here"
text_ids = tokenizer(text, return_tensors='pt').input_ids
model(text_ids)
```


## Using the pipeline
```python
# Use a pipeline as a high-level helper
from transformers import pipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = pipeline("text2text-generation", model="smji/ben2ipa-byt5small", device=device)


"""
  `texts` must be in the format of: <district> <contents>
"""
outputs = pipe(texts, max_length=1024, batch_size=batch_size)
```

## Credits
Done by [S M Jishanul Islam](https://github.com/S-M-J-I), [Sadia Ahmmed](https://github.com/sadia-ahmmed), [Sahid Hossain Mustakim](https://github.com/sratul35)