---
license: apache-2.0
language:
  - en
  - fa
tags:
  - translation
  - english-to-persian
  - persian-to-english
  - bilingual
model_type: llama
base_model: meta-llama/Llama-3.2-1B
widget:
  - text: |
      ### English:
      The children were playing in the park.
      ### Persian:
  - text: |
      ### Persian:
      من به مدرسه می‌روم.
      ### English:    
---


# LLaMA 3.2 1B – English ↔ Persian Translator

This model is a fine-tuned version of [`meta-llama/Llama-3.2-1B`](https://huggingface.co/meta-llama/Llama-3.2-1B), trained for **bidirectional translation** between **English and Persian**. It supports both:

- 🇬🇧 English → 🇮🇷 Persian
- 🇮🇷 Persian → 🇬🇧 English

---

## Format

The model expects prompts in the following format:

```
### English:
The children were playing in the park.
### Persian:
```
or

```
### Persian:
کودکان در پارک بازی می‌کردند.
### English:
```
---

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("Sheikhaei/llama-3.2-1b-en-fa-translator")
tokenizer = AutoTokenizer.from_pretrained("Sheikhaei/llama-3.2-1b-en-fa-translator")

prompt = """### English:
The children were playing in the park.
### Persian:
"""

inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100, do_sample=False)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## Training Data

This model was fine-tuned on a custom English–Persian parallel dataset containing ~640,000 sentence pairs. The source data was collected from Tatoeba and then translated and expanded using the Gemma-3-12B model.

## Evaluation

| Direction     | BLEU | COMET |
|---------------|------|------|
| English → Persian | 0.47 | 0.89 |
| Persian → English | 0.58 | 0.91 |

## License

Apache 2.0