--- {} --- # 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) ```