README.md

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# Luganda to English Informal Translation Model
This model translates informal Luganda sentences to English. It was trained on a dataset of Luganda proverbs with their English translations. The dataset consists of 3135 examples.

## Data
**Train:** The training data consists of 3135 Luganda proverbs and their corresponding English translations.
**Eval:** The evaluation data is part of the training data and consists of informal sentences.

## Model
**Architecture:** Seq2Seq
**Pretrained Model:** Helsinki-NLP/opus-mt-ug-en
**Fine-tuning:** The model was fine-tuned for 50 epochs with a learning rate of 2e-5.

## Translation
**Source Language:** Luganda
**Target Language:** English
**Domain:** Informal sentences and proverbs

## Usage
Here is an example of how to load and use the model for translation:

```python
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model_name = 'your_model_name_on_hf_hub'
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Example input sentence in Luganda
input_sentence = 'Olutalo lwa nsi yonna lwazibwa omwaka oguwedde.'

inputs = tokenizer(input_sentence, return_tensors='pt')
outputs = model.generate(**inputs)
translation = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(translation)
```