---
language:
- sw
- ha
- zu
- ki
- fr
- en
tags:
- gender-bias
- seq2seq
- text-generation
- african-nlp
- bias-correction
license: apache-2.0
---

# JuaKazi Multilingual Bias Corrector v1

Seq2seq gender bias correction model covering 6 languages.
Fine-tuned from `castorini/afriteva_v2_base` on ~10K correction pairs.

## Usage

Input format: `correct bias {lang}: {biased sentence}`

Where `lang` is one of: `sw`, `ha`, `zu`, `ki`, `fr`, `en`

```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("juakazike/multilingual-bias-corrector-v1")
model = AutoModelForSeq2SeqLM.from_pretrained("juakazike/multilingual-bias-corrector-v1")

def correct(text, lang):
    prompt = f"correct bias {lang}: {text}"
    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=128)
    out = model.generate(**inputs, max_new_tokens=128, num_beams=4)
    return tokenizer.decode(out[0], skip_special_tokens=True)

correct("The chairman will lead the board meeting.", "en")
# -> "The chair will lead the board meeting."
```

## Validation BLEU (val set, 10% held out per language)

| Language | Pairs | BLEU |
|----------|-------|------|
| Swahili (sw) | 1,586 | 17.7 |
| Hausa (ha) | 1,917 | 4.1 |
| Zulu (zu) | 1,931 | 0.6 |
| Gikuyu (ki) | 867 | 4.0 |
| French (fr) | 636 | 30.8 |
| English (en) | 3,464 | 38.6 |